collaborators

13 papers

cs.AI2026

: An End-to-End Agent Auditing Engine

Haoning Wang, Mingxun Zhang, Chenyue Yu +4

With the rapid advancement of large language models (LLMs), harnesses have become essential infrastructure for deploying agents across a wide range of domains. The fast-evolving ha…

cs.AI2026

Agent Skills Matter: Inferring Proprietary Skills from Execution Trajectories

Jianing Geng, Ruiqi He, Zekun Fei +6

Agent skills package reusable procedures that improve downstream performance. Their lightweight, portable form enables marketplace monetization and private deployment behind cloud-…

cs.AI2026

Do LLMs Know Their Vulnerable Scenarios?

Ziheng Peng, Huiqi Deng, Haoran Jing +5

Safety-aligned large language models are trained to refuse harmful requests, yet embedding the same requests in particular scenarios can bypass their safeguards. Existing red-teami…

cs.CL2026

Privacy-Preserving Text Sanitization for Distributed Agents Collaboration via Disentangled Representations

Xuan Liu, Hefeng Zhou, Sicheng Chen +6

When distributed agents exchange text across organizational boundaries, privacy leakage arises not only from explicit identifiers but also from distributional signatures such as fo…

cs.CR2026

PrivacyPeek: Auditing What LLM-Based Agents Acquire, Not Just What They Say

Mingxuan Zhang, Jiahui Han, Dadi Guo +5

LLM-based agents are rapidly advancing, autonomously invoking external tools to complete multi-step tasks for users. However, agents often acquire more sensitive information than t…

cs.AI2026

COLLEAGUE.SKILL: Automated AI Skill Generation via Expert Knowledge Distillation

Tianyi Zhou, Dongrui Liu, Leitao Yuan +2

LLM agents are increasingly expected not only to complete isolated tasks, but also to carry bounded representations of human expertise, judgment, and interaction style. Building su…