collaborators

16 papers

cs.AI2026

Probing the Misaligned Thinking Process of Language Models

Kaiwen Zhou, Constantin Venhoff, Jonathan Michala +2

Large language models exhibit a growing range of misaligned behaviors such as strategic deception, sandbagging, and self-preservation. As they are increasingly deployed in high-sta…

cs.CV2026

WorldMemArena: Evaluating Multimodal Agent Memory Through Action-World Interaction

Chengzhi Liu, Yuzhe Yang, Sophia Xiao Pu +14

Multimodal large language models are increasingly deployed as long-horizon agents, where memory must do more than recall: it must track an evolving world, revise what has gone stal…

cs.AI2026

Detecting Unfaithful Chain-of-Thought via Circuit-Guided Internal-External Discrepancy

Xu Shen, Zhen Tan, Song Wang +4

Chain-of-thought (CoT) reasoning improves the problem-solving ability of large language models (LLMs), but generated reasoning traces may not faithfully reflect the model's actual…

cs.AI2026

SkillEvolBench: Benchmarking the Evolution from Episodic Experience to Procedural Skills

Yingtie Lei, Zhongwei Wan, Jiankun Zhang +13

Large language model (LLM) agents accumulate rich episodic trajectories while solving real-world tasks, but it remains unclear whether such experience can be distilled into reusabl…

cs.CL2026

Auditing Agent Harness Safety

Chengzhi Liu, Yichen Guo, Yepeng Liu +8

LLM agents increasingly run inside execution harnesses that dispatch tools, allocate resources, and route messages between specialized components. However, a harness can return a c…

cs.AI2026

Stateful Reasoning via Insight Replay

Bin Lei, Caiwen Ding, Jiachen Yang +2

Chain-of-Thought (CoT) reasoning has become a foundation for eliciting multi-step reasoning in large language models, but recent studies show that its benefits do not scale monoton…