TsuGO: Probing Search Efficiency in LLM Reasoning via Go Life-and-Death Problems
The evaluation of LLM reasoning is moving from final-answer accuracy to process-level assessment, yet existing methods still fail to capture how models plan reasoning paths and allocate reasoning resources--that is, how they organize search. Prior process-level methods focus on the coherence and redundancy of chain-of-thought (CoT), and most benchmark tasks have a single objective solvable by static capabilities such as derivation and tool use, leaving search organization unmeasured. We introduce TsuGO, a process-level reasoning benchmark for evaluating Search Efficiency in LLM reasoning through Go life-and-death problems. These problems provide closed and verifiable solution spaces with ...
| Authors | Shunwen Bai, Ziping Ma, Chaoyang Zhang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 13 August 2026 |
| Last updated at source | 13 August 2026 |
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