5 papers
The Tasteful Agent: Measuring and Improving Taste in Long-Horizon Tasks
Wenbo Pan, Zhichao Liu, Shujie Liu +6
LLM agents increasingly work on long-horizon tasks, and the decisions they make along the way, such as which hypothesis to test or which implementation to build on, determine the o…
Dual-branch Robust Unlearnable Examples
Xianlong Wang, Hangtao Zhang, Wenbo Pan +4
Unlearnable examples (UEs) aim to compromise model training by injecting imperceptible perturbations to clean samples. However, existing UE schemes exhibit limited robustness again…
M: Every Task Deserves Its Own Memory Harness
Wenbo Pan, Shujie Liu, Xiangyang Zhou +4
Large language model agents rely on specialized memory systems to accumulate and reuse knowledge during extended interactions. Recent architectures typically adopt a fixed memory d…
WebTrap: Stealthy Mid-Task Hijacking of Browser Agents During Navigation
Zhichao Liu, Wenbo Pan, Haining Yu +3
Browser agents are increasingly deployed in long-horizon tasks, which require executing extended action chains to accomplish user goals. However, this prolonged execution process p…
Towards Long-Horizon Interpretability: Efficient and Faithful Multi-Token Attribution for Reasoning LLMs
Wenbo Pan, Zhichao Liu, Xianlong Wang +2
Token attribution methods provide intuitive explanations for language model outputs by identifying causally important input tokens. However, as modern LLMs increasingly rely on ext…