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dataset_info:
config_name: SODA_2026
features:
- name: question_id
dtype: string
- name: paper_id
dtype: string
- name: title
dtype: string
- name: venue
dtype: string
- name: year
dtype: int64
- name: node_id
dtype: string
- name: prompt_type
dtype: string
- name: problem
dtype: string
- name: answer
dtype: string
- name: answer_type
dtype: string
- name: answer_symbols
dtype: string
- name: answer_assumptions
dtype: string
- name: reference_solution
dtype: string
- name: difficulty
dtype: string
- name: topic_tags
dtype: string
- name: format_issues
dtype: string
- name: verification_method
dtype: string
- name: procedural_audit
dtype: string
- name: content_audit
dtype: string
- name: independent_verification
dtype: string
- name: equivalence_check
dtype: string
- name: source_dag_repo
dtype: string
- name: source_dag_config
dtype: string
- name: source_dag_split
dtype: string
- name: source_dag_revision
dtype: string
- name: source_dag_sha256
dtype: string
- name: generation_model
dtype: string
- name: generation_effort
dtype: string
- name: generation_prompt_version
dtype: string
- name: reused_from_four_question_run
dtype: bool
splits:
- name: test
num_bytes: 1165731
num_examples: 290
download_size: 545335
dataset_size: 1165731
configs:
- config_name: SODA_2026
data_files:
- split: test
path: SODA_2026/test-*
---
# TCSBench 2026: Final-answer problems
This release contains **290 exact-answer problems** from **142 SODA 2026 paper DAGs**. It is SODA-only, and answers are visible. The public config/split is `SODA_2026` / `test`.
## Coverage and curation
The generator requested three problems per DAG, each with a distinct theorem-like target node; quality gates did not force-fill unsuitable papers. After curation, 62 papers have three questions, 38 have two, 28 have one, and 14 have none. Thus 128 papers appear in the question rows. [`paper_coverage.json`](./paper_coverage.json) lists all source papers and their final counts.
This release was copied from the [original AI-Math-TCS release](https://huggingface.co/datasets/AI-Math-TCS/TCSBench_2026_ans), then the trailing answer-format instruction was removed from **every** public `problem`. The mathematical question, canonical answer, reference solution, audit fields, and `question_id` were otherwise preserved. **41 rows were excluded** because their canonical `answer` contains an integer literal of six or more decimal digits anywhere in the expression, including inside fractions or radicals. This is a textual literal rule, not an evaluation of symbolic expressions. The original source release remains available; this copy is the curated evaluation set.
Remaining answer types: 133 integer, 86 rational, 41 rational-expression, and 30 algebraic-expression. 1 retained row(s) have a `unicode_math` formatting flag, recorded in `format_issues`.
## Generation and checks
Problems were generated with `gpt-5.6-sol` at `xhigh` effort from a target node and its proof-relevant DAG context. Each accepted problem passed context and exact-answer eligibility checks, scaffold reduction, a proceduralness audit, an independent solve, answer-equivalence review, and a final content audit. The post-generation removal of the response-format instruction changes no mathematical assumptions or requested quantity, but these audits were not rerun on the edited string. Model-assisted audits are not a formal guarantee of mathematical correctness.
The `answer` column is the canonical closed-form answer; `reference_solution` explains it. `answer_symbols` and `answer_assumptions` are JSON strings used by the 0/1 grader. Exact symbolic comparison is attempted first, with `gpt-5.6-luna` at medium effort used only when exact comparison is unresolved. See the [grader](https://github.com/CohenQU/AI-Math-TCS/blob/6c1dc00/scripts/synthetic/final_answer_grader.py) and [equivalence fallback](https://github.com/CohenQU/AI-Math-TCS/blob/6c1dc00/scripts/synthetic/final_answer_equivalence.py).
## Provenance
Each row records its source paper and target node, generation settings, audit records, and the SHA-256 of the exact source DAG payload. The source is the [structurally validated SODA 2026 DAG split](https://huggingface.co/datasets/AI-Math-TCS/tcs_dags/viewer/SODA_2026/legacy_v1_6_structurally_repaired_gemini_3_8_flash) at revision `4ccf1e006ac1d6f3053049b7fcc5aa47cec8a6f8`.
```python
from datasets import load_dataset
ds = load_dataset("HerrHruby/TCSBench_2026_ans", "SODA_2026", split="test")
```
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