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cs.AI2026
LPS-Bench: Benchmarking Safety Awareness of Computer-Use Agents in Long-Horizon Planning under Benign and Adversarial Scenarios
Tianyu Chen, Chujia Hu, Ge Gao +3
Computer-use agents (CUAs) execute multi-stage tasks through tools, where an early unsafe decision can propagate to consequential actions. Evaluating only final outcomes can miss s…
cs.LG2026
Principled Fine-tuning of LLMs from User-Edits: A Medley of Preference, Supervision, and Reward
Dipendra Misra, Aldo Pacchiano, Ta-Chung Chi +1
We study how to fine-tune LLMs using user-edit deployment data consisting of a set of context, an agent's response, and user edits. This deployment data is naturally generated by u…