papers

Publications (23)

cs.SE2026

Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering

Chenyu Zhou, Huacan Chai, Wenteng Chen +18

Large language model (LLM) agents are increasingly built less by changing model weights than by reorganizing the runtime around them. Capabilities that earlier systems expected the…

cs.LG2026

Attributing and Exploiting Safety Vectors through Global Optimization in Large Language Models

Fengheng Chu, Jiahao Chen, Yuhong Wang +4

While Large Language Models (LLMs) are aligned to mitigate risks, their safety guardrails remain fragile against jailbreak attacks. This reveals limited understanding of components…

cs.LG2025

Accelerating Prefilling for Long-Context LLMs via Sparse Pattern Sharing

Dan Peng, Zhihui Fu, Zewen Ye +2

Sparse attention methods exploit the inherent sparsity in attention to speed up the prefilling phase of long-context inference, mitigating the quadratic complexity of full attentio…

cs.CL2026

When Agents "Misremember" Collectively: Exploring the Mandela Effect in LLM-based Multi-Agent Systems

Naen Xu, Hengyu An, Shuo Shi +7

Recent advancements in large language models (LLMs) have significantly enhanced the capabilities of collaborative multi-agent systems, enabling them to address complex challenges.…

cs.CR2026

FraudShield: Knowledge Graph Empowered Defense for LLMs against Fraud Attacks

Naen Xu, Jinghuai Zhang, Ping He +6

Large language models (LLMs) have been widely integrated into critical automated workflows, including contract review and job application processes. However, LLMs are susceptible t…

cs.CV2025

GreedyPrune: Retenting Critical Visual Token Set for Large Vision Language Models

Ruiguang Pei, Weiqing Sun, Zhihui Fu +1

Although Large Vision Language Models (LVLMs) have demonstrated remarkable performance in image understanding tasks, their computational efficiency remains a significant challenge,…