| --- |
| license: cc-by-4.0 |
| language: |
| - en |
| pretty_name: SYNC per-row experiment records |
| size_categories: |
| - 1M<n<10M |
| tags: |
| - language-models |
| - multi-agent-communication |
| - interpretability |
| --- |
| |
| # SYNC: per-row experiment records |
|
|
| Per-row records behind the paper **Share the Symbol, Not the Vector: Training-Free Fact Communication Across Language |
| Models** (Xin Li, Mengbing Liu, Hao Jiang, Xin Gao, Annan Wang, Xingwei Qu, Yichi Zhang, Chau Yuen). |
|
|
| - Paper: https://arxiv.org/abs/2610.19696 |
| - Project page: https://lixin.ai/SYNC/ |
| - Code: https://github.com/LiXin97/SYNC |
|
|
| ## Contents |
|
|
| 1.6 million rows in 322 JSON-lines files (2.3 GB). One row per scene, world, question and condition: the receiver, the |
| message source and arm, the write configuration, the parsed answer, correctness, coverage, the generated text and the |
| message content. To fit the size limit, token ids, slot tables, per-layer patch reports and most cache/logit hashes |
| were removed from the full rows; every point estimate in the paper can be recounted from these rows, and the |
| engineering checks that need the removed fields are recorded in the analysis outputs of the code repository. |
| Rows of the Countries task omit message contents. |
|
|
| The folder layout mirrors the code repository, so the files land where its scripts expect them: |
|
|
| | Folder | Study | |
| |---|---| |
| | `artifacts/latest0924/expA/` | new senders and receivers (Table 1) | |
| | `artifacts/latest0924/predict/` | depth prediction (Table 2) | |
| | `artifacts/latest0924/layout/`, `artifacts/latest0924/realtask/` | new layouts and the Countries task (Table 3) | |
| | `artifacts/latest0924/graded/`, `artifacts/latest0924/graded_textfmt/` | graded weights and other text formats (Figure 6) | |
| | `artifacts/latest0924/diag/` | late-writing diagnostics | |
| | `artifacts/receiver_recovery/` | development receivers (Figures 4-5) | |
| | `artifacts/word_interface_followup/` | four-object questions and simpler representations | |
|
|
| ## Usage |
|
|
| ```bash |
| git clone https://github.com/LiXin97/SYNC.git && cd SYNC |
| hf download XINLI1997/SYNC-data --repo-type dataset --local-dir . |
| python scripts/latest0924/layout/recount_layout.py |
| python scripts/latest0924/predict/score.py |
| ``` |
|
|
| ## How the data were made |
|
|
| Every scene is generated mechanically from fixed word lists and a seeded random generator; no third-party text and no |
| personal data are included. The Countries task follows the published protocol of Ramesh & Li (2025) and is rebuilt |
| from hand-written lists of landmarks and countries. The model outputs were produced by open-weight models (Qwen, |
| gpt-oss, Gemma, Llama, GLM, Mistral, Granite, OLMo and Seed-OSS checkpoints); text generated by a model remains subject |
| to that model's license. |
|
|
| ## License |
|
|
| CC BY 4.0. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{li2026sync, |
| title = {Share the Symbol, Not the Vector: Training-Free Fact Communication Across Language Models}, |
| author = {Xin Li and Mengbing Liu and Hao Jiang and Xin Gao and Annan Wang and Xingwei Qu and Yichi Zhang and Chau Yuen}, |
| year = {2026}, |
| eprint = {2610.19696}, |
| archivePrefix = {arXiv}, |
| primaryClass = {cs.CL}, |
| url = {https://arxiv.org/abs/2610.19696} |
| } |
| ``` |
|
|
