Author

Tong-Yao Zhu

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#machine learning Preprint Oct 2025

Why Do LLM Agents Fail in Exploring New Environments? A World-Modeling Perspective

Across unseen environments, SPA consistently and substantially improves over vanilla RL: for example, it raises the Sokoban success rate from 25.6% to 59.8% on Qwen2.5-1.5B-Instruct, letting sub-3B models surpass a 20B baseline on these tasks.

Shiqi Chen, Tong-Yao Zhu, Zian Wang et al. · 27 citations · ⚡7

#artificial intelligence Review Sep 2026

When Models Edit Too Much: On the Fidelity of Minimal Code Edits

This work constructs an evaluation framework from 400 BigCodeBench problems by injecting controlled AST-level corruptions into reference solutions, giving each repair task a known minimal patch, and positions edit fidelity as a distinct axis of code-repair quality and shows that it can be measured and learned.

Tong-Yao Zhu, Wei-Lun Lim, Min-Yen Kan · 0 citations