activity
20242026
collaborators

22 papers

cs.AI2026

Don't Solve, Just Compare: Tiny Advisors for Runtime Intervention in LLM Agents

Yanze Jiang, Mingxuan Li, Yuhao Wang +2

LLM agents are emerging as an important paradigm for real-world tasks that require reasoning, tool use, and sequential decision-making. As these agents operate over longer horizons…

cs.CR2026

AliMark: Enhancing Robustness of Sentence-Level Watermarking Against Text Paraphrasing

Yuexin Li, Wenjie Qu, Linyu Wu +5

Existing sentence-level watermarking methods enhance robustness to paraphrasing by anchoring watermarks in sentence semantics. However, their prefix-based designs remain vulnerable…

cs.CR2026

Echoes within the Reasoning: Stealthy and Effective Watermarking via Chain of Thought

Jiacheng Lu, Yiming Li, Tao Song +4

Large Language Models with Chain-of-Thought reasoning capabilities represent valuable intellectual property, yet existing black-box watermarking methods often trade robustness for…

cs.AI2026

AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration

Jiaqi Liu, Shi Qiu, Mairui Li +33

Automating scientific discovery requires more than generating papers from ideas. Real research is iterative: hypotheses are challenged from multiple perspectives, experiments fail…

cs.CR2026

Securing LLM Agents Need Intent-to-Execution Integrity

Wenjie Qu, Ming Xu, Peiran Wang +3

This position paper argues that securing LLM agents requires first defining an end-to-end correctness property that specifies when an agent's execution faithfully reflects the user…

cs.CR2026

SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness

Jiahao Huo, Wenjie Qu, Yibo Yan +5

Semantic-level watermarking (SWM) improves robustness against text modifications by treating sentences as the basic unit. However, robustness to paragraph-level paraphrasing remain…