Datasets:

qvac
/

GenesisIII

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-# QVAC Genesis III: A Large-Scale, High-Quality Open Synthetic STEM Corpus for Efficient Language Model Pre-Training
-<h4 align="left">
-  📄 <a href="https://arxiv.org/abs/2609.19513">Paper (arXiv)</a> · 🤗 <a href="https://huggingface.co/datasets/qvac/GenesisIII">Hugging Face Dataset</a> · 💻 <a href="https://github.com/tether-ai-research/qvac-genesis-III">GitHub</a>
-</h4>
-## Key highlights
-- **Peer-Reviewed at COLM 2026:** The [QVAC Genesis III paper](https://arxiv.org/abs/2609.19513) from Tether AI Research was accepted at the Conference on Language Modeling (COLM) 2026, providing peer-reviewed recognition of the corpus, methodology, and controlled evaluation.
-- **An Expanding Research Program:** Genesis I introduced **40.91B tokens** and Failure Analysis. Genesis II added **107.46B new tokens** and Option-Level Reasoning, bringing Genesis I and II to **148.37B tokens across 19 domains**. Genesis III adds a further **43.06B tokens**, expanding the corpus to **191.43B tokens**, and validates the combined methodology through the controlled experiments presented in the COLM 2026 paper.
-- **Large-Scale STEM Coverage:** QVAC Genesis III contains **191.43 billion tokens and approximately 160 million documents** across 19 STEM domains, three difficulty levels—**high school, college, and professional**—and four educational styles.
-- **Learning from Both Failures and Successes:** A dual generation strategy uses a weak student model to determine what each example should teach. Failures become targeted corrective explanations, while successes become contrastive analyses of every answer option.
-- **Two Complementary Training Splits:** The corpus contains **108.67B Option-Level (OL) tokens**, generated from correctly answered questions, and **82.76B Failure Analysis (FA) tokens**, generated from incorrect or non-extractable answers.
-- **Large Gains Under a Matched Token Budget:** Against a token-matched Cosmopedia-v2 run, the combined Genesis III corpus improves accuracy by **28.57 points on ARC-Easy**, **21.35 points on ARC-Challenge**, **2.52 points on GPQA Diamond**, and **15.03 points on MMLU STEM**.
-- **Near-Perfect Answer Extractability:** The OL split reaches a **99.45% Valid Answer Rate (VAR)** on MMLU STEM, meaning nearly every response contains one clear, extractable final answer.
-- **QVAC Genesis III** is made available by Tether AI Research under the CC-BY-NC 4.0 (Creative Commons Attribution–NonCommercial 4.0), allowing free use and adaptation for non-commercial research and educational purposes while ensuring appropriate credit to us. A model trained on the combined Option-Level (OL) and Failure Analysis (FA) tokens is also being released on the Apache 2.0 license for research and education purposes.
-**Copyright Complaints:** We will take appropriate actions in response to notice of copyright infringement. If you believe your work has been used or copied in a manner that infringes upon your intellectual property rights, please email [data-apps@tether.io](mailto:data-apps@tether.io) identifying and describing both the copyrighted work and alleged infringing content to file a notice of infringement.
-<div align="center" style="background:#f4f6f9; border:1px solid #e5e9ef; border-radius:12px; padding:24px 28px; margin:28px 0;">
-  <h3 style="margin:0 0 8px 0; font-size:20px; color:#111;">🚀 QVAC Genesis III on Hugging Face</h3>
-  <p style="margin:0 0 16px 0; color:#555;">Access the QVAC Genesis III dataset and resources in one place.</p>
-  <a href="https://huggingface.co/collections/qvac/genesis-iii" style="display:inline-block; background:#1f7feb; color:#ffffff; padding:10px 22px; margin:4px; border-radius:8px; text-decoration:none; font-weight:600;">🔗 Open the Collection</a>
-</div>
-## 1. Introduction
-High-quality STEM pre-training data remains scarce in the open ecosystem. This is particularly limiting for small language models intended for edge and on-device deployment, where both model capacity and training-token budgets are constrained.
-[QVAC Genesis I](https://huggingface.co/blog/qvac/genesis-i) introduced Tether Data, S.A. de C.V.’s (Tether AI Research, we, our)  Learning from Failures approach: incorrect student answers were turned into educational explanations that diagnose the error and teach the correct solution. [QVAC Genesis II](https://huggingface.co/blog/qvac/genesis-ii) added Option-Level Reasoning, which uses correctly answered questions to explain why the correct option works and why every distractor fails.
-QVAC Genesis III develops this dual approach into a 191.43B-token corpus and evaluates it through controlled from-scratch pre-training experiments. The accompanying paper, **accepted at COLM 2026**, also introduces an LLM-as-a-parser evaluation protocol that separates answer correctness from the ability to produce a clear, extractable final answer.
-## 2. Building QVAC Genesis III
-The generation pipeline has four stages:
-1. Acquire and quality-filter domain-specific seed passages.
-2. Generate self-contained multiple-choice questions.
-3. Ask an edge-scale student model to answer each question and extract its final choice.
-4. Route the example to Failure Analysis or Option-Level Reasoning.
-![pipeline](https://cdn-uploads.huggingface.co/production/uploads/66ad47f5a45133da70d1c40b/Ha8so8hEmzOpkPWHfbMo3.png)
-### 2.1 Seeds and question generation
-Seed passages are sampled from [FineFineWeb](https://huggingface.co/datasets/m-a-p/FineFineWeb) and filtered with the [Ultra-FineWeb classifier](https://huggingface.co/openbmb/Ultra-FineWeb-classifier). Sampling continues until approximately 500,000 high-quality seeds remain.
-[QwQ-32B](https://huggingface.co/Qwen/QwQ-32B) then generates self-contained questions with exactly four mutually exclusive options and one gold label. The prompt enforces an even distribution of correct labels across A, B, C, and D. A lightweight format validator rejects approximately 15% of raw generations.
-### 2.2 Turning student behavior into training data
-The data-generation student is [Qwen3-1.7B-Base](https://huggingface.co/Qwen/Qwen3-1.7B-Base), selected after comparison with Llama-3.2-1B, Gemma-3-1B, and SmolLM2-1.7B on the target STEM benchmarks.
-The student produces a free-form answer to each generated question. CompassJudger-2-32B parses the response and returns one option label, `NO_ANSWER` when no choice is extractable, or `MULTIPLE_ANSWERS` when conflicting final choices remain. This parser extracts the student's committed choice; it does not solve or grade the question.
-The extracted choice determines the route:
-- **Failure Analysis (FA):** An incorrect or non-extractable response is sent to QwQ-32B together with the question, student response, and gold answer. The teacher diagnoses the likely error, explains the correction, and produces a self-contained lesson.
-- **Option-Level Reasoning (OL):** A correctly answered question is sent to QwQ-32B with its options and gold answer. The teacher produces a self-contained analysis that justifies the correct option and explicitly refutes every distractor.
-Both routes render content in four styles: educational textbook, web article, question-answer tutoring, and conversational dialogue.
-## 3. Corpus composition
-| Split | Tokens | Documents |
-| :---- | ----: | ----: |
-| Option-Level Reasoning | 108.67B | 92,538,646 |
-| Failure Analysis | 82.76B | 67,107,907 |
-| **Total** | **191.43B** | **159,646,553** |
-The corpus covers 19 curriculum-aligned domains:
-- Astronomy
-- Electrical engineering
-- High school geography
-- College biology
-- High school biology
-- College medicine
-- Professional medicine
-- College mathematics
-- High school mathematics
-- College physics
-- High school physics
-- Conceptual physics
-- College chemistry
-- High school chemistry
-- College computer science
-- High school computer science
-- Machine learning
-- High school statistics
-- Econometrics
-The three difficulty levels are high school, college, and professional.
-### Deduplication and decontamination
-MinHash near-deduplication with 60-gram signatures flags 47,927 duplicate pairs. Of these, only **1,729 unique documents** are identified as near-duplicates, less than 0.002% of the corpus.
-The corpus is also scanned against the benchmark sets included in the paper's decontamination analysis with AllenAI's Decon overlap detector. A document is marked as contaminated when answer overlap is at least 60% with meaningful term matches or passage overlap is at least 40%.
-- **17 verified contaminated documents** among 159.6M Genesis III documents, compared with 313 among 39.1M Cosmopedia-v2 documents.
-- All 17 Genesis III matches are in the FA split; the OL split has **zero** verified contamination.
-- GSM8K test leakage is **0%**.
-- MMLU test leakage is **0.005%**: 3 matches among 56,168 examples.
-## 4. Evaluation: parsing, not judging
-Standard multiple-choice evaluation often scores the likelihood of answer tokens without testing what the model actually generates. Genesis III instead uses a generation-first protocol built on [OpenCompass](https://github.com/open-compass/opencompass):
-1. The evaluated model generates a free-form response.
-2. A separate extractor model recovers the final committed option or abstains.
-3. The extracted option is compared with the benchmark gold label.
-![eval](https://cdn-uploads.huggingface.co/production/uploads/66ad47f5a45133da70d1c40b/yXNs5LmZd8exbbj_w6xFV.png)
-We report two metrics:
-- **Accuracy:** the percentage of all examples for which the extracted option matches the gold label. Missing or conflicting answers count as incorrect.
-- **Valid Answer Rate (VAR):** the percentage of responses containing one unambiguous, extractable option.
-Within this parser-based protocol, VAR measures answer extractability separately from correctness.
-## 5. Controlled pre-training experiments
-The primary controlled runs use the Qwen3-1.7B architecture initialized from random weights. Training hyperparameters are identical across runs, making data composition the primary experimental variable; token budgets are reported separately below.
-The models are trained with Megatron-Core and Megatron-Bridge using Flash Attention 2, BF16 precision, a sequence length of 4,096, and packed sequences with attention resets at document boundaries. Training runs on 64 NVIDIA H100 80GB GPUs.
-We evaluate on:
-- ARC-Easy and ARC-Challenge
-- GPQA Diamond
-- The 19 MMLU STEM domains aligned with the Genesis III curriculum
-These benchmarks are intentionally STEM-aligned with the training distribution. The paper excludes non-STEM MMLU domains because Genesis III does not cover them.
-### 5.1 Individual split ablation
-The OL and Cosmopedia-v2 runs have closely matched token budgets. The FA run is approximately 25% smaller by design.
-| Model / training data | Training tokens | ARC-E | ARC-C | GPQA | MMLU STEM accuracy | MMLU STEM VAR |
-| :---- | ----: | ----: | ----: | ----: | ----: | ----: |
-| Cosmopedia-v2, 4 epochs | ~109.7B | 20.63 | 21.02 | 17.67 | 20.39 | 72.71 |
-| Genesis III — FA, 1 epoch | 82.76B | 29.81 | 23.05 | 21.21 | 23.29 | 78.14 |
-| Genesis III — OL, 1 epoch | 108.67B | **47.44** | **36.27** | **27.78** | **30.26** | **99.45** |
-| **OL improvement over Cosmopedia-v2** |  | **+26.81** | **+15.25** | **+10.11** | **+9.87** | **+26.74** |
-Both Genesis III splits outperform the same four-epoch Cosmopedia-v2 baseline on every reported benchmark. OL and Cosmopedia-v2 have closely matched token budgets; FA achieves its gains with approximately 25% fewer tokens. OL is the stronger standalone split, while FA shows that incorrect and ambiguous student responses still provide useful pre-training signal.
-![genesis_split_ablation](https://cdn-uploads.huggingface.co/production/uploads/66ad47f5a45133da70d1c40b/9xYFP3QhUMrCKBuVGKPbh.png)
-### 5.2 Full corpus against baselines
-The combined Genesis III run uses one epoch over 191.43B tokens. Its controlled baseline is a token-matched Cosmopedia-v2 run. We also report the publicly released [Cosmo-1B](https://huggingface.co/HuggingFaceTB/cosmo-1b), an uncontrolled comparison: Cosmo-1B has 1.8B parameters and was trained on 180B tokens including additional code, mathematics, instruction-following, and chat-formatted data.
-| Model / training data | Training tokens | ARC-E | ARC-C | GPQA | MMLU STEM accuracy | MMLU STEM VAR |
-| :---- | ----: | ----: | ----: | ----: | ----: | ----: |
-| Cosmopedia-v2, 7 epochs | ~192.4B | 23.28 | 21.36 | 20.20 | 15.16 | 62.48 |
-| Cosmo-1B | 180B | 28.04 | 23.73 | 19.70 | 25.42 | **92.51** |
-| Genesis III Combined, 1 epoch | 191.43B | **51.85** | **42.71** | **22.72** | **30.19** | 92.06 |
-| **Improvement over Cosmopedia-v2** |  | **+28.57** | **+21.35** | **+2.52** | **+15.03** | **+29.58** |
-| **Improvement over Cosmo-1B** |  | **+23.81** | **+18.98** | **+3.02** | **+4.77** | −0.45 |
-The combined model improves accuracy over both baselines on all four benchmark groups. Its VAR is 29.58 points above the token-matched Cosmopedia-v2 run and 0.45 points below Cosmo-1B, which the paper describes as comparable. The reported results are point estimates without confidence intervals, so small differences should not be read as evidence of statistical significance.
-![genesis_combined_comparison](https://cdn-uploads.huggingface.co/production/uploads/66ad47f5a45133da70d1c40b/eaGZc_nKwJcZai0JVmtOL.png)
-## 6. What the ablations show
-Three findings stand out:
-1. **Successes and failures carry different signals.** OL outperforms FA in 18 of 19 MMLU STEM domains, while FA is stronger in Professional Medicine. On High School Geography, the full 191.43B-token combined run reaches 35.4% accuracy, compared with 31.8% for the 108.67B-token OL run and 25.8% for the 82.76B-token FA run.
-2. **Structured option-level data improves answer extractability.** OL reaches 100% VAR in 15 of 19 MMLU STEM domains and 99.45% overall on MMLU STEM. Its conflicting-answer rate is only 0.06%.
-3. **The gains transfer across architectures.** Repeating the OL-versus-Cosmopedia-v2 comparison with Llama-3.2-1B, SmolLM2-1.7B, and Gemma-3-1B improves every reported metric for every tested backbone.
-![genesis_cross_architecture](https://cdn-uploads.huggingface.co/production/uploads/66ad47f5a45133da70d1c40b/_ZWQYc7wYG4wMQnPpjtML.png)
-Additional checks support the main result:
-- At the closest same-stage checkpoint, corresponding to approximately 25B Cosmopedia-v2 tokens, OL improves over Cosmopedia-v2 by 20.80 points on MMLU STEM, 15.93 on ARC-C, 16.94 on ARC-E, and 8.08 on GPQA Diamond.
-- Re-parsing saved MMLU predictions with GPT-OSS-20B and GPT-OSS-120B preserves OL's VAR advantage over the seven-epoch Cosmopedia-v2 endpoint. Across CompassJudger-2-32B and the two independent extractors, that advantage is 24.28–36.97 points.
-## 7. Conclusion
-QVAC Genesis III is a 191.43B-token synthetic STEM corpus designed to make each pre-training token more useful for small, efficient language models. Its dual pipeline turns failures into corrections and successes into exhaustive option-level explanations. Controlled from-scratch experiments show consistent gains over Cosmopedia-v2, while the separate, uncontrolled Cosmo-1B comparison shows higher Genesis III accuracy on the reported benchmarks. The LLM-as-a-parser protocol makes response validity measurable rather than implicit.
-Together with [Genesis I](https://huggingface.co/blog/qvac/genesis-i) and [Genesis II](https://huggingface.co/blog/qvac/genesis-ii), Genesis III continues our work on open pre-training data and models for education and STEM reasoning, with Genesis III specifically targeting efficient edge and on-device models.
-## References
-1. QVAC. [QVAC Genesis I: the Largest and Highest-Quality Multi-domain Educational Synthetic Dataset for Pre-training](https://huggingface.co/blog/qvac/genesis-i).
-2. QVAC. [QVAC Genesis II: Expanding the Largest and Highest-Quality Multi-domain Educational Synthetic Dataset for LLM Pre-training](https://huggingface.co/blog/qvac/genesis-ii).
-3. Hugging Face. [Cosmopedia: How to Create Large-Scale Synthetic Data for Pre-training](https://huggingface.co/blog/cosmopedia).
-4. M-A-P. [FineFineWeb](https://huggingface.co/datasets/m-a-p/FineFineWeb).
-5. Wang et al. [Ultra-FineWeb: Efficient Data Filtering and Verification for High-Quality LLM Training Data](https://arxiv.org/abs/2505.05427).
-6. OpenCompass Contributors. [OpenCompass](https://github.com/open-compass/opencompass).
-7. Clark et al. [Think You Have Solved Question Answering? Try ARC](https://arxiv.org/abs/1803.05457).
-8. Rein et al. [GPQA: A Graduate-Level Google-Proof Q&A Benchmark](https://arxiv.org/abs/2311.12022).
-9. Hendrycks et al. [Measuring Massive Multitask Language Understanding](https://arxiv.org/abs/2009.03300).
-## Citation
-If you use QVAC Genesis III in your work, please cite:
-```bibtex
-@misc{vitabile2026qvacgenesisiii,
-  title         = {QVAC Genesis III: A Large-Scale, High-Quality Open Synthetic STEM Corpus for Efficient Language Model Pre-Training},
-  author        = {Davide Vitabile and Nikhil Ranjan and Akshay Nambiar and Kamal Kumar Gupta and Amril Nazir},
-  year          = {2026},
-  eprint        = {2609.19513},
-  archivePrefix = {arXiv},
-  primaryClass  = {cs.AI},
-  institution   = {Tether Data, S.A. de C.V. d.b.a. Tether AI Research},
-  note          = {Accepted at the Conference on Language Modeling (COLM) 2026},
-  url           = {https://arxiv.org/abs/2609.19513}
-}
-```
-**Licensing Information:** This QVAC Genesis III dataset is licensed by Tether Data, S.A. de C.V. under the CC-BY-NC 4.0 ([https://creativecommons.org/licenses/by-nc/4.0/legalcode.en](https://creativecommons.org/licenses/by-nc/4.0/legalcode.en)). As described above, the data was generated using FineFineWeb ([https://huggingface.co/datasets/m-a-p/FineFineWeb](https://huggingface.co/datasets/m-a-p/FineFineWeb)) licensed under the [Apache 2.0](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md) license, the Ultra-FineWeb-classifier ([https://huggingface.co/openbmb/Ultra-FineWeb-classifier](https://huggingface.co/openbmb/Ultra-FineWeb-classifier)) licensed under the [Apache 2.0 license](https://choosealicense.com/licenses/apache-2.0/), QwQ-32B ([https://huggingface.co/Qwen/QwQ-32B](https://huggingface.co/Qwen/QwQ-32B)) licensed under the [Apache 2.0](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md) license and Qwen/Qwen3-1.7B-Base ([https://huggingface.co/Qwen/Qwen3-1.7B-Base](https://huggingface.co/Qwen/Qwen3-1.7B-Base)) licensed under the [Apache 2.0](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md) license.
-FineFineWeb data was generated from FineWeb data ([ODC-BY 1.0](https://opendatacommons.org/licenses/by/1-0/)) using data that originated in Common Crawl ([Creative Commons terms](https://commoncrawl.org/terms-of-use)). The FineFineWeb authors used Qwen2-7B licensed under the [Apache-2.0 license](https://choosealicense.com/licenses/apache-2.0/), Qwen 2-72B-Instruct licensed under the [Tongyi Qianwen license](https://huggingface.co/Qwen/Qwen2-72B-Instruct/blob/main/LICENSE), and a BERT model licensed under the [Apache 2.0 license](https://choosealicense.com/licenses/apache-2.0/).
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-For the avoidance of doubt, this Section [4](https://creativecommons.org/licenses/by-nc/4.0/legalcode.en#s4) supplements and does not replace Your obligations under this Public License where the Licensed Rights include other Copyright and Similar Rights.
-**Section 5 – Disclaimer of Warranties and Limitation of Liability.**
-1. **Unless otherwise separately undertaken by the Licensor, to the extent possible, the Licensor offers the Licensed Material as-is and as-available, and makes no representations or warranties of any kind concerning the Licensed Material, whether express, implied, statutory, or other. This includes, without limitation, warranties of title, merchantability, fitness for a particular purpose, non-infringement, absence of latent or other defects, accuracy, or the presence or absence of errors, whether or not known or discoverable. Where disclaimers of warranties are not allowed in full or in part, this disclaimer may not apply to You.**
-2. **To the extent possible, in no event will the Licensor be liable to You on any legal theory (including, without limitation, negligence) or otherwise for any direct, special, indirect, incidental, consequential, punitive, exemplary, or other losses, costs, expenses, or damages arising out of this Public License or use of the Licensed Material, even if the Licensor has been advised of the possibility of such losses, costs, expenses, or damages. Where a limitation of liability is not allowed in full or in part, this limitation may not apply to You.**
-3. The disclaimer of warranties and limitation of liability provided above shall be interpreted in a manner that, to the extent possible, most closely approximates an absolute disclaimer and waiver of all liability.
-**Section 6 – Term and Termination.**
-1. This Public License applies for the term of the Copyright and Similar Rights licensed here. However, if You fail to comply with this Public License, then Your rights under this Public License terminate automatically.
-2. Where Your right to use the Licensed Material has terminated under Section 6(a), it reinstates:
-   1. automatically as of the date the violation is cured, provided it is cured within 30 days of Your discovery of the violation; or
-   2. upon express reinstatement by the Licensor.
-For the avoidance of doubt, this Section [6(b)](https://creativecommons.org/licenses/by-nc/4.0/legalcode.en#s6b) does not affect any right the Licensor may have to seek remedies for Your violations of this Public License.
-3. For the avoidance of doubt, the Licensor may also offer the Licensed Material under separate terms or conditions or stop distributing the Licensed Material at any time; however, doing so will not terminate this Public License.
-4. Sections [1](https://creativecommons.org/licenses/by-nc/4.0/legalcode.en#s1) , [5](https://creativecommons.org/licenses/by-nc/4.0/legalcode.en#s5) , [6](https://creativecommons.org/licenses/by-nc/4.0/legalcode.en#s6) , [7](https://creativecommons.org/licenses/by-nc/4.0/legalcode.en#s7) , and [8](https://creativecommons.org/licenses/by-nc/4.0/legalcode.en#s8) survive termination of this Public License.
-**Section 7 – Other Terms and Conditions.**
-1. The Licensor shall not be bound by any additional or different terms or conditions communicated by You unless expressly agreed.
-2. Any arrangements, understandings, or agreements regarding the Licensed Material not stated herein are separate from and independent of the terms and conditions of this Public License.
-**Section 8 – Interpretation.**
-1. For the avoidance of doubt, this Public License does not, and shall not be interpreted to, reduce, limit, restrict, or impose conditions on any use of the Licensed Material that could lawfully be made without permission under this Public License.
-2. To the extent possible, if any provision of this Public License is deemed unenforceable, it shall be automatically reformed to the minimum extent necessary to make it enforceable. If the provision cannot be reformed, it shall be severed from this Public License without affecting the enforceability of the remaining terms and conditions.
-3. No term or condition of this Public License will be waived and no failure to comply consented to unless expressly agreed to by the Licensor.
-4. Nothing in this Public License constitutes or may be interpreted as a limitation upon, or waiver of, any privileges and immunities that apply to the Licensor or You, including from the legal processes of any jurisdiction or authority.
-## **Apache License**
-Version 2.0, January 2004
-[http://www.apache.org/licenses/](http://www.apache.org/licenses/)
-TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
-1. **Definitions.**
-   "**License**" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document.
-   "**Licensor**" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License.
-   "**Legal Entity**" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "**control**" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity.
-   "**You**" (or "**Your**") shall mean an individual or Legal Entity exercising permissions granted by this License.
-   "**Source**" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files.
-   "**Object**" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types.
-   "**Work**" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below).
-   "**Derivative Works**" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof.
-   "**Contribution**" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "**submitted**" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "**Not a Contribution**."
-   "**Contributor**" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work.
-2. **Grant of Copyright License**. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form.
-3. **Grant of Patent License**. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed.
-4. **Redistribution**. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions:
-   (a)   You must give any other recipients of the Work or Derivative Works a copy of this License; and
-   (b)   You must cause any modified files to carry prominent notices stating that You changed the files; and
-   (c)   You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and
-   (d)   If the Work includes a "**NOTICE**" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License.
-   You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License.
-5. **Submission of Contributions**. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions.
-6. **Trademarks**. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file.
-7. **Disclaimer of Warranty**. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License.
-8. **Limitation of Liability**. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages.
-9. **Accepting Warranty or Additional Liability.** While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability.
-END OF TERMS AND CONDITIONS
-**Open Data Commons Attribution License (ODC-By) v1.0**
-https://opendatacommons.org/licenses/by/1-0/
-**DISCLAIMER**
-Open Data Commons is not a law firm and does not provide legal services of any kind.
-Open Data Commons has no formal relationship with you. Your receipt of this document does not create any kind of agent-client relationship. Please seek the advice of a suitably qualified legal professional licensed to practice in your jurisdiction before using this document.
-No warranties and disclaimer of any damages. This information is provided ‘as is‘, and this site makes no warranties on the information provided. Any damages resulting from its use are disclaimed.
-A plain language summary of the ODC Attribution License (ODC-BY) is available as well as a plain text version.
-**Attribution License (ODC-By)**
-**PREAMBLE**
-The Open Data Commons Attribution License is a license agreement intended to allow users to freely share, modify, and use this Database subject only to the attribution requirements set out in Section 4\.
-Databases can contain a wide variety of types of content (images, audiovisual material, and sounds all in the same database, for example), and so this license only governs the rights over the Database, and not the contents of the Database individually. Licensors may therefore wish to use this license together with another license for the contents.
-Sometimes the contents of a database, or the database itself, can be covered by other rights not addressed here (such as private contracts, trademark over the name, or privacy rights / data protection rights over information in the contents), and so you are advised that you may have to consult other documents or clear other rights before doing activities not covered by this License.
-The Licensor (as defined below) and You (as defined below) agree as follows:
-**1.0 DEFINITIONS OF CAPITALISED WORDS**
-��Collective Database” – Means this Database in unmodified form as part of a collection of independent databases in themselves that together are assembled into a collective whole. A work that constitutes a Collective Database will not be considered a Derivative Database.
-“Convey” – As a verb, means Using the Database, a Derivative Database, or the Database as part of a Collective Database in any way that enables a Person to make or receive copies of the Database or a Derivative Database. Conveying does not include interaction with a user through a computer network, or creating and Using a Produced Work, where no transfer of a copy of the Database or a Derivative Database occurs.
-“Contents” – The contents of this Database, which includes the information, independent works, or other material collected into the Database. For example, the contents of the Database could be factual data or works such as images, audiovisual material, text, or sounds.
-“Database” – A collection of material (the Contents) arranged in a systematic or methodical way and individually accessible by electronic or other means offered under the terms of this License.
-“Database Directive” – Means Directive 96/9/EC of the European Parliament and of the Council of 11 March 1996 on the legal protection of databases, as amended or succeeded.
-“Database Right” – Means rights resulting from the Chapter III (“sui generis”) rights in the Database Directive (as amended and as transposed by member states), which includes the Extraction and Re-utilisation of the whole or a Substantial part of the Contents, as well as any similar rights available in the relevant jurisdiction under Section 10.4.
-“Derivative Database” – Means a database based upon the Database, and includes any translation, adaptation, arrangement, modification, or any other alteration of the Database or of a Substantial part of the Contents. This includes, but is not limited to, Extracting or Re-utilising the whole or a Substantial part of the Contents in a new Database.
-“Extraction” – Means the permanent or temporary transfer of all or a Substantial part of the Contents to another medium by any means or in any form.
-“License” – Means this license agreement and is both a license of rights such as copyright and Database Rights and an agreement in contract.
-“Licensor” – Means the Person that offers the Database under the terms of this License.
-“Person” – Means a natural or legal person or a body of persons corporate or incorporate.
-“Produced Work” – a work (such as an image, audiovisual material, text, or sounds) resulting from using the whole or a Substantial part of the Contents (via a search or other query) from this Database, a Derivative Database, or this Database as part of a Collective Database.
-“Publicly” – means to Persons other than You or under Your control by either more than 50% ownership or by the power to direct their activities (such as contracting with an independent consultant).
-“Re-utilisation” – means any form of making available to the public all or a Substantial part of the Contents by the distribution of copies, by renting, by online or other forms of transmission.
-“Substantial” – Means substantial in terms of quantity or quality or a combination of both. The repeated and systematic Extraction or Re-utilisation of insubstantial parts of the Contents may amount to the Extraction or Re-utilisation of a Substantial part of the Contents.
-“Use” – As a verb, means doing any act that is restricted by copyright or Database Rights whether in the original medium or any other; and includes without limitation distributing, copying, publicly performing, publicly displaying, and preparing derivative works of the Database, as well as modifying the Database as may be technically necessary to use it in a different mode or format.
-“You” – Means a Person exercising rights under this License who has not previously violated the terms of this License with respect to the Database, or who has received express permission from the Licensor to exercise rights under this License despite a previous violation.
-Words in the singular include the plural and vice versa.
-**2.0 WHAT THIS LICENSE COVERS**
-2.1 Legal effect of this document. This License is:
-a.     A license of applicable copyright and neighbouring rights;
-b.     A license of the Database Right; and
-c.     An agreement in contract between You and the Licensor.
-2.2 Legal rights covered. This License covers the legal rights in the Database, including:
-a.     Copyright. Any copyright or neighbouring rights in the Database. The copyright licensed includes any individual elements of the Database, but does not cover the copyright over the Contents independent of this Database. See Section 2.4 for details. Copyright law varies between jurisdictions, but is likely to cover: the Database model or schema, which is the structure, arrangement, and organisation of the Database, and can also include the Database tables and table indexes; the data entry and output sheets; and the Field names of Contents stored in the Database;
-b.     Database Rights. Database Rights only extend to the Extraction and Re-utilisation of the whole or a Substantial part of the Contents. Database Rights can apply even when there is no copyright over the Database. Database Rights can also apply when the Contents are removed from the Database and are selected and arranged in a way that would not infringe any applicable copyright; and
-c.     Contract. This is an agreement between You and the Licensor for access to the Database. In return you agree to certain conditions of use on this access as outlined in this License.
-2.3 Rights not covered.
-a.     This License does not apply to computer programs used in the making or operation of the Database;
-b.     This License does not cover any patents over the Contents or the Database; and
-c.     This License does not cover any trademarks associated with the Database.
-2.4 Relationship to Contents in the Database. The individual items of the Contents contained in this Database may be covered by other rights, including copyright, patent, data protection, privacy, or personality rights, and this License does not cover any rights (other than Database Rights or in contract) in individual Contents contained in the Database.
-For example, if used on a Database of images (the Contents), this License would not apply to copyright over individual images, which could have their own separate licenses, or one single license covering all of the rights over the images.
-**3.0 RIGHTS GRANTED**
-3.1 Subject to the terms and conditions of this License, the Licensor grants to You a worldwide, royalty-free, non-exclusive, terminable (but only under Section 9\) license to Use the Database for the duration of any applicable copyright and Database Rights. These rights explicitly include commercial use, and do not exclude any field of endeavour. To the extent possible in the relevant jurisdiction, these rights may be exercised in all media and formats whether now known or created in the future.
-The rights granted cover, for example:
-a.     Extraction and Re-utilisation of the whole or a Substantial part of the Contents;
-b.     Creation of Derivative Databases;
-c.     Creation of Collective Databases;
-d.     Creation of temporary or permanent reproductions by any means and in any form, in whole or in part, including of any Derivative Databases or as a part of Collective Databases; and
-e.     Distribution, communication, display, lending, making available, or performance to the public by any means and in any form, in whole or in part, including of any Derivative Database or as a part of Collective Databases.
-3.2 Compulsory license schemes. For the avoidance of doubt:
-a.     Non-waivable compulsory license schemes. In those jurisdictions in which the right to collect royalties through any statutory or compulsory licensing scheme cannot be waived, the Licensor reserves the exclusive right to collect such royalties for any exercise by You of the rights granted under this License;
-b.     Waivable compulsory license schemes. In those jurisdictions in which the right to collect royalties through any statutory or compulsory licensing scheme can be waived, the Licensor waives the exclusive right to collect such royalties for any exercise by You of the rights granted under this License; and,
-c.     Voluntary license schemes. The Licensor waives the right to collect royalties, whether individually or, in the event that the Licensor is a member of a collecting society that administers voluntary licensing schemes, via that society, from any exercise by You of the rights granted under this License.
-3.3 The right to release the Database under different terms, or to stop distributing or making available the Database, is reserved. Note that this Database may be multiple-licensed, and so You may have the choice of using alternative licenses for this Database. Subject to Section 10.4, all other rights not expressly granted by Licensor are reserved.
-**4.0 CONDITIONS OF USE**
-4.1 The rights granted in Section 3 above are expressly made subject to Your complying with the following conditions of use. These are important conditions of this License, and if You fail to follow them, You will be in material breach of its terms.
-4.2 Notices. If You Publicly Convey this Database, any Derivative Database, or the Database as part of a Collective Database, then You must:
-a.     Do so only under the terms of this License;
-b.     Include a copy of this License or its Uniform Resource Identifier (URI) with the Database or Derivative Database, including both in the Database or Derivative Database and in any relevant documentation;
-c.     Keep intact any copyright or Database Right notices and notices that refer to this License; and
-d.     If it is not possible to put the required notices in a particular file due to its structure, then You must include the notices in a location (such as a relevant directory) where users would be likely to look for it.
-4.3 Notice for using output (Contents). Creating and Using a Produced Work does not require the notice in Section 4.2. However, if you Publicly Use a Produced Work, You must include a notice associated with the Produced Work reasonably calculated to make any Person that uses, views, accesses, interacts with, or is otherwise exposed to the Produced Work aware that Content was obtained from the Database, Derivative Database, or the Database as part of a Collective Database, and that it is available under this License.
-a.     Example notice. The following text will satisfy notice under Section 4.3:
-Contains information from DATABASE NAME which is made available under the ODC Attribution License.
-DATABASE NAME should be replaced with the name of the Database and a hyperlink to the location of the Database. “ODC Attribution License” should contain a hyperlink to the URI of the text of this License. If hyperlinks are not possible, You should include the plain text of the required URI’s with the above notice.
-4.4 Licensing of others. You may not sublicense the Database. Each time You communicate the Database, the whole or Substantial part of the Contents, or any Derivative Database to anyone else in any way, the Licensor offers to the recipient a license to the Database on the same terms and conditions as this License. You are not responsible for enforcing compliance by third parties with this License, but You may enforce any rights that You have over a Derivative Database. You are solely responsible for any modifications of a Derivative Database made by You or another Person at Your direction. You may not impose any further restrictions on the exercise of the rights granted or affirmed under this License.
-**5.0 MORAL RIGHTS**
-5.1 Moral rights. This section covers moral rights, including any rights to be identified as the author of the Database or to object to treatment that would otherwise prejudice the author’s honour and reputation, or any other derogatory treatment:
-a.     For jurisdictions allowing waiver of moral rights, Licensor waives all moral rights that Licensor may have in the Database to the fullest extent possible by the law of the relevant jurisdiction under Section 10.4;
-b.     If waiver of moral rights under Section 5.1 a in the relevant jurisdiction is not possible, Licensor agrees not to assert any moral rights over the Database and waives all claims in moral rights to the fullest extent possible by the law of the relevant jurisdiction under Section 10.4; and
-c.     For jurisdictions not allowing waiver or an agreement not to assert moral rights under Section 5.1 a and b, the author may retain their moral rights over certain aspects of the Database.
-Please note that some jurisdictions do not allow for the waiver of moral rights, and so moral rights may still subsist over the Database in some jurisdictions.
-**6.0 FAIR DEALING, DATABASE EXCEPTIONS, AND OTHER RIGHTS NOT AFFECTED**
-6.1 This License does not affect any rights that You or anyone else may independently have under any applicable law to make any use of this Database, including without limitation:
-a.     Exceptions to the Database Right including: Extraction of Contents from non-electronic Databases for private purposes, Extraction for purposes of illustration for teaching or scientific research, and Extraction or Re-utilisation for public security or an administrative or judicial procedure.
-b.     Fair dealing, fair use, or any other legally recognised limitation or exception to infringement of copyright or other applicable laws.
-6.2 This License does not affect any rights of lawful users to Extract and Re-utilise insubstantial parts of the Contents, evaluated quantitatively or qualitatively, for any purposes whatsoever, including creating a Derivative Database (subject to other rights over the Contents, see Section 2.4). The repeated and systematic Extraction or Re-utilisation of insubstantial parts of the Contents may however amount to the Extraction or Re-utilisation of a Substantial part of the Contents.
-**7.0 WARRANTIES AND DISCLAIMERS**
-7.1 The Database is licensed by the Licensor “as is” and without any warranty of any kind, either express, implied, or arising by statute, custom, course of dealing, or trade usage. Licensor specifically disclaims any and all implied warranties or conditions of title, non-infringement, accuracy or completeness, the presence or absence of errors, fitness for a particular purpose, merchantability, or otherwise. Some jurisdictions do not allow the exclusion of implied warranties, so this exclusion may not apply to You.
-**8.0 LIMITATION OF LIABILITY**
-8.1 Subject to any liability that may not be excluded or limited by law, the Licensor is not liable for, and expressly excludes, all liability for loss or damage however and whenever caused to anyone by any use under this License, whether by You or by anyone else, and whether caused by any fault on the part of the Licensor or not. This exclusion of liability includes, but is not limited to, any special, incidental, consequential, punitive, or exemplary damages such as loss of revenue, data, anticipated profits, and lost business. This exclusion applies even if the Licensor has been advised of the possibility of such damages.
-8.2 If liability may not be excluded by law, it is limited to actual and direct financial loss to the extent it is caused by proved negligence on the part of the Licensor.
-**9.0 TERMINATION OF YOUR RIGHTS UNDER THIS LICENSE**
-9.1 Any breach by You of the terms and conditions of this License automatically terminates this License with immediate effect and without notice to You. For the avoidance of doubt, Persons who have received the Database, the whole or a Substantial part of the Contents, Derivative Databases, or the Database as part of a Collective Database from You under this License will not have their licenses terminated provided their use is in full compliance with this License or a license granted under Section 4.8 of this License. Sections 1, 2, 7, 8, 9 and 10 will survive any termination of this License.
-9.2 If You are not in breach of the terms of this License, the Licensor will not terminate Your rights under it.
-9.3 Unless terminated under Section 9.1, this License is granted to You for the duration of applicable rights in the Database.
-9.4 Reinstatement of rights. If you cease any breach of the terms and conditions of this License, then your full rights under this License will be reinstated:
-a.     Provisionally and subject to permanent termination until the 60th day after cessation of breach;
-b.     Permanently on the 60th day after cessation of breach unless otherwise reasonably notified by the Licensor; or
-c.     Permanently if reasonably notified by the Licensor of the violation, this is the first time You have received notice of violation of this License from the Licensor, and You cure the violation prior to 30 days after your receipt of the notice.
-9.5 Notwithstanding the above, Licensor reserves the right to release the Database under different license terms or to stop distributing or making available the Database. Releasing the Database under different license terms or stopping the distribution of the Database will not withdraw this License (or any other license that has been, or is required to be, granted under the terms of this License), and this License will continue in full force and effect unless terminated as stated above.
-**10.0 GENERAL**
-10.1 If any provision of this License is held to be invalid or unenforceable, that must not affect the validity or enforceability of the remainder of the terms and conditions of this License and each remaining provision of this License shall be valid and enforced to the fullest extent permitted by law.
-10.2 This License is the entire agreement between the parties with respect to the rights granted here over the Database. It replaces any earlier understandings, agreements or representations with respect to the Database.
-10.3 If You are in breach of the terms of this License, You will not be entitled to rely on the terms of this License or to complain of any breach by the Licensor.
-10.4 Choice of law. This License takes effect in and will be governed by the laws of the relevant jurisdiction in which the License terms are sought to be enforced. If the standard suite of rights granted under applicable copyright law and Database Rights in the relevant jurisdiction includes additional rights not granted under this License, these additional rights are granted in this License in order to meet the terms of this License.
-## **Tongyi Qianwen LICENSE AGREEMENT**
-Tongyi Qianwen Release Date: August 3, 2023
-By clicking to agree or by using or distributing any portion or element of the Tongyi Qianwen Materials, you will be deemed to have recognized and accepted the content of this Agreement, which is effective immediately.
-1. **Definitions**
-   1. This Tongyi Qianwen LICENSE AGREEMENT (this "**Agreement**") shall mean the terms and conditions for use, reproduction, distribution and modification of the Materials as defined by this Agreement.
-   2. "**We**" (or "**Us**") shall mean Alibaba Cloud.
-   3. "**You**" (or "**Your**") shall mean a natural person or legal entity exercising the rights granted by this Agreement and/or using the Materials for any purpose and in any field of use.
-   4. "**Third Parties**" shall mean individuals or legal entities that are not under common control with Us or You.
-   5. "**Tongyi Qianwen**" shall mean the large language models (including Qwen model and Qwen-Chat model), and software and algorithms, consisting of trained model weights, parameters (including optimizer states), machine-learning model code, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Us.
-   6. "**Materials**" shall mean, collectively, Alibaba Cloud's proprietary Tongyi Qianwen and Documentation (and any portion thereof) made available under this Agreement.
-   7. "**Source**" form shall mean the preferred form for making modifications, including but not limited to model source code, documentation source, and configuration files.
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-2. Grant of Rights
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README.md CHANGED Viewed

@@ -893,37 +893,29 @@ configs:
 ---
 # QVAC Genesis III
-This repository contains the QVAC Genesis III dataset associated with the
-COLM 2026 paper
-[QVAC Genesis III: A Large-Scale, High-Quality Open Synthetic STEM Corpus for Efficient Language Model Pre-Training](https://arxiv.org/abs/2609.19513).
-| Resource | Link |
-| -------- | ---- |
-| 📄 Paper (COLM 2026) | [arXiv:2609.19513](https://arxiv.org/abs/2609.19513) |
-| 📝 Blog | [huggingface.co/blog/qvac/genesis-iii](https://huggingface.co/blog/qvac/genesis-iii) |
-| 💻 Code | [github.com/tether-ai-research/qvac-genesis-III](https://github.com/tether-ai-research/qvac-genesis-III) |
-| 🤗 Models | [huggingface.co/collections/qvac/genesis-iii](https://huggingface.co/collections/qvac/genesis-iii) |
 QVAC Genesis III is a large-scale synthetic STEM corpus for efficient language-model pre-training. It contains **159,646,553 educational documents** and approximately **191 billion training tokens** across 19 curriculum-aligned domains, two complementary generation pipelines, and four educational writing styles.
-![QVAC Genesis III synthetic-data generation pipeline, from seed acquisition and multiple-choice question generation through student answering, LLM parsing, Option-Level Reasoning, and Failure Analysis](https://cdn-uploads.huggingface.co/production/uploads/66ad47f5a45133da70d1c40b/Ha8so8hEmzOpkPWHfbMo3.png)
-## 📋 Dataset Details
-| Field | Value |
-| ----- | ----- |
-| **Curated by** | Davide Vitabile, Nikhil Ranjan, Akshay Nambiar, Kamal Kumar Gupta, and Amril Nazir |
-| **Organization** | Tether Data, S.A. de C.V. (Tether AI Research) |
-| **Shared by** | QVAC |
-| **Language** | English |
-| **License** | CC BY-NC 4.0 |
-| **Scale** | 159,646,553 documents and approximately 191 billion training tokens |
-| **Domains** | 19 STEM domains |
-| **Generation methods** | Failure Analysis and Option-Level Reasoning |
-| **Styles** | educational textbook, web article, question-answer tutoring, and conversational dialogue |
-## ✨ What Genesis III Adds
 QVAC Genesis III uses both successful and unsuccessful answers from an edge-scale student model as generation signals:
@@ -934,18 +926,7 @@ Both pipelines render their output in four styles to increase structural and ped
 Under controlled training settings, models trained from scratch on Failure Analysis, Option-Level Reasoning, and their combination substantially improve ARC, GPQA Diamond, and MMLU STEM performance over token-matched Cosmopedia-v2 baselines.
-![QVAC Genesis III Combined compared with Cosmo-1B and the seven-epoch Cosmopedia-v2 baseline on ARC-Easy, ARC-Challenge, GPQA Diamond, MMLU STEM accuracy, and MMLU STEM Valid Answer Rate](https://cdn-uploads.huggingface.co/production/uploads/66ad47f5a45133da70d1c40b/eaGZc_nKwJcZai0JVmtOL.png)
-## 🧪 Research Checkpoints
-Models trained in the paper's controlled from-scratch experiments:
-| Checkpoint | Role | Hugging Face |
-| ---------- | ---- | ------------ |
-| 🔍 Failure Analysis | FA data ablation | [qvac-genesis-iii-qwen3-1.7b-fa](https://huggingface.co/qvac/qvac-genesis-iii-qwen3-1.7b-fa) |
-| 🧠 Option-Level | OL data ablation | [qvac-genesis-iii-qwen3-1.7b-ol](https://huggingface.co/qvac/qvac-genesis-iii-qwen3-1.7b-ol) |
-| 🔗 Combined FA+OL | Full Genesis III mix | [qvac-genesis-iii-qwen3-1.7b-combined](https://huggingface.co/qvac/qvac-genesis-iii-qwen3-1.7b-combined) |
-## 🗂️ Dataset Configurations
 The dataset has one `train` split and 20 configurations:
@@ -956,21 +937,31 @@ The configurations reference the same underlying Parquet files; selecting a doma
 ### Domains
-| | | |
-| --- | --- | --- |
-| `astronomy` | `college_biology` | `college_chemistry` |
-| `college_computer_science` | `college_maths` | `college_medicine` |
-| `college_physics` | `conceptual_physics` | `econometrics` |
-| `electronic_science` | `geography` | `high_school_biology` |
-| `high_school_chemistry` | `high_school_computer_science` | `high_school_maths` |
-| `high_school_physics` | `high_school_statistics` | `machine_learning` |
-| `professional_medicine` | | |
 Release identifiers preserve two source-directory names:
 `electronic_science` corresponds to **electrical engineering**, and
 `geography` corresponds to **high school geography**.
-## 🧱 Dataset Structure
 Each row contains the final self-contained training document and explicit metadata:
@@ -998,7 +989,7 @@ Illustrative, abridged example:
 }
 ```
-## 🚀 How to Load
 The full corpus is very large. Streaming is strongly recommended unless you intentionally want a local copy.
@@ -1040,7 +1031,7 @@ textbook = astronomy.filter(
 )
 ```
-## 🏗️ Dataset Creation
 ### 1. Seed acquisition and quality filtering
@@ -1064,12 +1055,12 @@ Incorrect and non-extractable responses were routed to Failure Analysis. Correct
 - conversational dialogue.
 The complete methodology and prompt templates are documented in the
-[Genesis III publication](https://arxiv.org/abs/2609.19513).
-## 🛡️ Content Safety and Personal Information
-The complete corpus was scanned before
-release. The scan covered all source text fields rather than a sample:
 - The toxicity pipeline used **Detoxify** for broad screening and
   **Qwen3Guard-Gen-8B** for contextual review of flagged passages.
@@ -1089,11 +1080,11 @@ no toxicity-based removals were necessary.
 These automated and model-assisted scans can produce false positives or false
 negatives. Redaction may also affect a small amount of non-personal text that
-resembles an identifier. The scan addresses toxicity and personal information;
 it does not establish factual correctness, copyright clearance, or suitability
-for a particular downstream use. Although automated cleaning, filtering, and deduplication were applied, the dataset was not exhaustively audited for personal, sensitive, offensive, or otherwise harmful content. Users should perform additional screening appropriate to their use of the dataset.
-## 🧹 Deduplication and Benchmark Decontamination
 - MinHash near-deduplication with 60-gram signatures flagged 47,927 candidate pairs and identified 1,729 unique near-duplicate documents, less than 0.002% of the corpus.
 - AllenAI Decon overlap checks identified 17 verified benchmark-contaminated documents across the corpus.
@@ -1102,12 +1093,11 @@ for a particular downstream use. Although automated cleaning, filtering, and ded
 These automatic and manually reviewed checks quantify known overlap but cannot prove that the corpus is free of all benchmark material. The retention or removal status of the identified near-duplicates and benchmark matches must be confirmed before publication.
-## 🎯 Uses
-### ✅ Direct Use
-The dataset is intended for research and education purposes and in connection with those uses, for:
 - pre-training and continual pre-training of language models;
 - research on synthetic educational and STEM data;
@@ -1115,7 +1105,7 @@ The dataset is intended for research and education purposes and in connection wi
 - curriculum construction by domain, pipeline, or educational style;
 - research on token-efficient training of small language models.
-### 🚫 Out-of-Scope Use
 The dataset should not be treated as:
@@ -1127,7 +1117,7 @@ The dataset should not be treated as:
 Models trained on this corpus require independent domain-specific and safety evaluation before deployment.
-## ⚠️ Bias, Risks, and Limitations
 - The documents are synthetic and may contain hallucinations, reasoning errors, contradictory explanations, or incorrect answer keys.
 - Generator, student, parser, and filtering models can transmit their own biases and systematic errors.
@@ -1141,34 +1131,36 @@ Models trained on this corpus require independent domain-specific and safety eva
 Users should inspect and filter the corpus for their specific use case.
-## ⚖️ Licensing
-Licensing Information: This QVAC Genesis III dataset is licensed by Tether Data, S.A. de C.V. under the CC-BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/legalcode.en). As described in the blog post (https://huggingface.co/blog/qvac/genesis-iii/), the data was generated using FineFineWeb (https://huggingface.co/datasets/m-a-p/FineFineWeb) licensed under the Apache 2.0 license, the Ultra-FineWeb-classifier (https://huggingface.co/openbmb/Ultra-FineWeb-classifier) licensed under the Apache 2.0 license, QwQ-32B (https://huggingface.co/Qwen/QwQ-32B) licensed under the Apache 2.0 license and Qwen/Qwen3-1.7B-Base (https://huggingface.co/Qwen/Qwen3-1.7B-Base) licensed under the Apache 2.0 license.
-FineFineWeb data was generated from FineWeb data (ODC-BY 1.0) using data that originated in Common Crawl (Creative Commons terms). The FineFineWeb authors used Qwen2-7B licensed under the Apache-2.0 license, Qwen 2-72B-Instruct licensed under the Tongyi Qianwen license, and a BERT model licensed under the Apache 2.0 license.
 Users are responsible for reviewing the applicable licenses and terms of these upstream resources. The dataset is provided as-is, without warranties of factual accuracy, fitness for a particular purpose, or non-infringement.
-## 📮 Copyright Complaints
 We will take appropriate action in response to notices of copyright infringement. If you believe your work has been used or copied in a way that infringes your intellectual-property rights, email [data-apps@tether.io](mailto:data-apps@tether.io) and identify the copyrighted work and the allegedly infringing material.
-## 📖 Citation
 ```bibtex
 @misc{vitabile2026qvacgenesisiii,
-  title         = {QVAC Genesis III: A Large-Scale, High-Quality Open Synthetic STEM Corpus for Efficient Language Model Pre-Training},
-  author        = {Davide Vitabile and Nikhil Ranjan and Akshay Nambiar and Kamal Kumar Gupta and Amril Nazir},
-  year          = {2026},
-  eprint        = {2609.19513},
-  archivePrefix = {arXiv},
-  primaryClass  = {cs.AI},
-  institution   = {Tether Data, S.A. de C.V. d.b.a. Tether AI Research},
-  note          = {Accepted at the Conference on Language Modeling (COLM) 2026},
-  url           = {https://arxiv.org/abs/2609.19513}
 }
 ```
-## ✉️ Dataset Card Contact
 Questions and feedback can be submitted through the [QVAC organization on Hugging Face](https://huggingface.co/qvac). Copyright complaints should be sent to [data-apps@tether.io](mailto:data-apps@tether.io).

 ---
 # QVAC Genesis III
+<h4 align="left">
+  📄 <a href="https://openreview.net/pdf?id=ZgtdqlpCU9">Paper (OpenReview)</a> · 📝 <a href="https://huggingface.co/blog/qvac/genesis-iii">Hugging Face Blog</a>
+</h4>
+---
 QVAC Genesis III is a large-scale synthetic STEM corpus for efficient language-model pre-training. It contains **159,646,553 educational documents** and approximately **191 billion training tokens** across 19 curriculum-aligned domains, two complementary generation pipelines, and four educational writing styles.
+Genesis III was introduced in **“QVAC Genesis III: A Large-Scale, High-Quality Open Synthetic STEM Corpus for Efficient Language Model Pre-Training,” accepted at the Conference on Language Modeling (COLM) 2026**.
+## Dataset Details
+- **Curated by:** Davide Vitabile, Nikhil Ranjan, Akshay Nambiar, Kamal Kumar Gupta, and Amril Nazir
+- **Organization:** Tether Data, S.A. de C.V. (Tether AI Research)
+- **Shared by:** QVAC
+- **Language:** English
+- **License:** CC BY-NC 4.0
+- **Scale:** 159,646,553 documents and approximately 191 billion training tokens
+- **Domains:** 19 STEM domains
+- **Generation methods:** Failure Analysis and Option-Level Reasoning
+- **Styles:** educational textbook, web article, question-answer tutoring, and conversational dialogue
+## What Genesis III Adds
 QVAC Genesis III uses both successful and unsuccessful answers from an edge-scale student model as generation signals:
 Under controlled training settings, models trained from scratch on Failure Analysis, Option-Level Reasoning, and their combination substantially improve ARC, GPQA Diamond, and MMLU STEM performance over token-matched Cosmopedia-v2 baselines.
+## Dataset Configurations
 The dataset has one `train` split and 20 configurations:
 ### Domains
+- `astronomy`
+- `college_biology`
+- `college_chemistry`
+- `college_computer_science`
+- `college_maths`
+- `college_medicine`
+- `college_physics`
+- `conceptual_physics`
+- `econometrics`
+- `electronic_science`
+- `geography`
+- `high_school_biology`
+- `high_school_chemistry`
+- `high_school_computer_science`
+- `high_school_maths`
+- `high_school_physics`
+- `high_school_statistics`
+- `machine_learning`
+- `professional_medicine`
 Release identifiers preserve two source-directory names:
 `electronic_science` corresponds to **electrical engineering**, and
 `geography` corresponds to **high school geography**.
+## Dataset Structure
 Each row contains the final self-contained training document and explicit metadata:
 }
 ```
+## How to Load
 The full corpus is very large. Streaming is strongly recommended unless you intentionally want a local copy.
 )
 ```
+## Dataset Creation
 ### 1. Seed acquisition and quality filtering
 - conversational dialogue.
 The complete methodology and prompt templates are documented in the
+[Genesis III publication](https://openreview.net/forum?id=ZgtdqlpCU9).
+## Content Safety and Personal Information
+The complete corpus was scanned for toxicity and personal information before
+release. The audit covered all source text fields rather than a sample:
 - The toxicity pipeline used **Detoxify** for broad screening and
   **Qwen3Guard-Gen-8B** for contextual review of flagged passages.
 These automated and model-assisted scans can produce false positives or false
 negatives. Redaction may also affect a small amount of non-personal text that
+resembles an identifier. The audit addresses toxicity and personal information;
 it does not establish factual correctness, copyright clearance, or suitability
+for a particular downstream use.
+## Deduplication and Benchmark Decontamination
 - MinHash near-deduplication with 60-gram signatures flagged 47,927 candidate pairs and identified 1,729 unique near-duplicate documents, less than 0.002% of the corpus.
 - AllenAI Decon overlap checks identified 17 verified benchmark-contaminated documents across the corpus.
 These automatic and manually reviewed checks quantify known overlap but cannot prove that the corpus is free of all benchmark material. The retention or removal status of the identified near-duplicates and benchmark matches must be confirmed before publication.
+## Uses
+### Direct Use
+The dataset is intended for:
 - pre-training and continual pre-training of language models;
 - research on synthetic educational and STEM data;
 - curriculum construction by domain, pipeline, or educational style;
 - research on token-efficient training of small language models.
+### Out-of-Scope Use
 The dataset should not be treated as:
 Models trained on this corpus require independent domain-specific and safety evaluation before deployment.
+## Bias, Risks, and Limitations
 - The documents are synthetic and may contain hallucinations, reasoning errors, contradictory explanations, or incorrect answer keys.
 - Generator, student, parser, and filtering models can transmit their own biases and systematic errors.
 Users should inspect and filter the corpus for their specific use case.
+## Licensing
+QVAC Genesis III is made available by Tether Data, S.A. de C.V. under the [Creative Commons Attribution-NonCommercial 4.0 International License](https://creativecommons.org/licenses/by-nc/4.0/) to the extent that Tether Data holds the applicable copyright and database rights. Seed material derives from FineFineWeb, FineWeb, and Common Crawl and may be subject to separate rights or terms; this license does not grant rights that Tether Data does not hold.
+The generation pipeline uses or builds on the following resources:
+- FineFineWeb and its upstream FineWeb/Common Crawl sources;
+- the Ultra-FineWeb classifier;
+- QwQ-32B;
+- Qwen3-1.7B-Base;
+- CompassJudger-2-32B-Instruct.
 Users are responsible for reviewing the applicable licenses and terms of these upstream resources. The dataset is provided as-is, without warranties of factual accuracy, fitness for a particular purpose, or non-infringement.
+## Copyright Complaints
 We will take appropriate action in response to notices of copyright infringement. If you believe your work has been used or copied in a way that infringes your intellectual-property rights, email [data-apps@tether.io](mailto:data-apps@tether.io) and identify the copyrighted work and the allegedly infringing material.
+## Citation (Provisional)
 ```bibtex
 @misc{vitabile2026qvacgenesisiii,
+  title     = {QVAC Genesis III: A Large-Scale, High-Quality Open Synthetic STEM Corpus for Efficient Language Model Pre-Training},
+  author    = {Davide Vitabile and Nikhil Ranjan and Akshay Nambiar and Kamal Kumar Gupta and Amril Nazir},
+  year      = {2026},
+  note      = {Accepted at the Conference on Language Modeling (COLM) 2026},
+  url       = {https://openreview.net/forum?id=ZgtdqlpCU9}
 }
 ```
+## Dataset Card Contact
 Questions and feedback can be submitted through the [QVAC organization on Hugging Face](https://huggingface.co/qvac). Copyright complaints should be sent to [data-apps@tether.io](mailto:data-apps@tether.io).