arXiv AI By Tidor-Vlad Pricope

RetroChessBench: A Benchmark for Reconstructing and Proving Chess Histories

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RetroChessBench is a 12‑task benchmark designed to evaluate language models on retrograde chess reasoning, requiring the reconstruction of legal game histories and the distinction between possible and forced events. The benchmark includes exact‑length constructions, unique endings, exhaustive answer sets, references, rubrics, and a terminal‑reward environment. In tests, GPT‑6 Astra High failed to produce correct final answers in 22 of 24 attempts without tools and 18 of 24 with code execution, highlighting significant reasoning failures even in rule‑governed tasks.

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arXiv AI
Aug 18

Rethinking Generalization in Reasoning SFT: A Conditional Analysis on Optimization, Data, and Model Capability

arXiv:2604. 06628v2 Announce Type: replace Abstract: A prevailing narrative in LLM post-training holds that supervised finetuning (SFT) memorizes while reinforcement learning (RL) generalizes.

By Qihan Ren, Peng Wang, Ruikun Cai, Shuai Shao, Dadi Guo, Yuejin Xie, Yafu Li, Quanshi Zhang, Xia Hu, Jing Shao, Dongrui Liu