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cs.AI2026

MemAudit: Post-hoc Auditing of Poisoned Agent Memory via Causal Attribution and Structural Anomaly Detection

Zhewen Tan, Yilun Yao, Huiyan Jin +9

Large language model agents increasingly rely on persistent memory to store past interactions, retrieve relevant demonstrations, and improve long-horizon task execution. However, t…

cs.AI2026

Formal Skill: Programmable Runtime Skills for Efficient and Accurate LLM Agents

Xi Zhang, Meijun Gao, Yuntian Zhao +6

Large Language Model (LLM) agents increasingly act inside real workspaces, where tools and skills determine whether model reasoning becomes reliable action. Existing skills remain…

cs.AI2026

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction

Pujun Feng, Xiaoyu Guo, Seyed Ehsan Saffari +10

Clinical decision-making is a feedback system where risk estimates influence treatment, which in turn changes disease trajectories, and both shape clinicians' measurement practices…

cs.AI2026

Thinking with Reasoning Skills: Fewer Tokens, More Accuracy

Guangxiang Zhao, Qilong Shi, Xusen Xiao +3

Reasoning LLMs often spend substantial tokens on long intermediate reasoning traces (e.g., chain-of-thought) when solving new problems. We propose to summarize and store reusable r…

cs.AI2025

Reverse-Engineered Reasoning for Open-Ended Generation

Haozhe Wang, Haoran Que, Qixin Xu +9

While the ``deep reasoning'' paradigm has spurred significant advances in verifiable domains like mathematics, its application to open-ended, creative generation remains a critical…