works on

From the 1 of 7 linked papers with an AI index.

collaborators

7 papers

cs.MA2026

BRA-Audit: Budgeted Runtime Auditing for LLM Multi-Agent Systems via Cumulative-Exposure Audit-Point Placement

Kaixiang Wang, Yidan Lin, Jiong Lou +1

LLM-based multi-agent systems (LLM-MAS) solve complex tasks through specialized collaboration, but inter-agent dependencies can propagate hallucinated or malicious outputs into sys…

cs.LG2026

Stop When Memory Suffices: Evidence-Conditioned Progressive Execution for LLM Agents

Yidan Lin, Kaixiang Wang, Jiong Lou +1

The continued development of LLMs toward persistent and adaptive intelligence increasingly requires long-term memory mechanisms that preserve and reuse information across interacti…

cs.AI2026

Deep Interaction: An Efficient Human-AI Interaction Method for Large Reasoning Models

Hefeng Zhou, Jinxuan Zhang, Jiong Lou +4

The paper introduces Deep Interaction, a method that lets users directly edit the chain‑of‑thought output of large language models to fix reasoning errors, resulting in higher corr…

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.AI2026

E-mem: Multi-agent based Episodic Context Reconstruction for LLM Agent Memory

Kaixiang Wang, Yidan Lin, Jiong Lou +3

The evolution of Large Language Model (LLM) agents towards System~2 reasoning, characterized by deliberative, high-precision problem-solving, requires maintaining rigorous logical…

cs.NI2026

IEMAS: An Incentive-Efficiency Routing Framework for Open Agentic Web Ecosystems

Hongze Liu, Chang Guo, Yingzeng Li +6

The transition to open, distributed Multi-Agent Systems (MAS) promises scalable intelligence but introduces a non-trivial tension: maximizing global efficiency requires cooperative…