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TCS-BENCH: Benchmarking State-of-the-Art Generative AI Theoretical Computer Science Research Ability

2026-08-10 · arXiv: 2608.09538

One-line summary

An AI research paper on TCS-BENCH: Benchmarking State-of-the-Art Generative AI Theoretical Computer Science Research Ability.

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Chinese explanation / 中文解读

中文解读待补充:本站会优先为大语言模型、生成式AI、ChatGPT相关技术、计算机视觉、深度学习等高价值论文补充中文说明。

Original abstract

We introduce TCS-Bench, a benchmark for evaluating Large Language Models (LLMs) on research-level Theoretical Computer Science (TCS) proof generation. TCS-Bench consists of theorem-proving tasks from papers published at top theoretical computer science venues (STOC, FOCS, and SODA). Each task provides the necessary context to derive a self-contained proof for a target result. We evaluate state-of-the-art models on this benchmark. We verify the correctness of generated proofs via a verification agent, and further benchmark the verifier against human-expert proof judgements on a set of target statements and generated proofs pairs. Our reference verifier achieves over 90% accuracy on the expert labeled set.

5.0Engineering value
7.0Research novelty
4.0Business relevance

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