4 citations · 7 across the 14 of their papers we have counts for
15 papers
SkillGrad: Optimizing Agent Skills Like Gradient Descent
Hanyu Wang, Yifan Lan, Bochuan Cao +2
Agent skills provide a lightweight way to adapt LLM agents to specialized domains by storing reusable procedural knowledge in structured files. However, whether downloaded from thi…
The Illusion of Reasoning: Exposing Evasive Data Contamination in LLMs via Zero-CoT Truncation
Yifan Lan, Yuanpu Cao, Hanyu Wang +2
Large language models (LLMs) have demonstrated impressive reasoning abilities across a wide range of tasks, but data contamination undermines the objective evaluation of these capa…
ReLope: From Hidden-State Probing to a Decision Module for Multimodal LLM Routing
Yaopei Zeng, Congchao Wang, Blake JianHang Chen +1
Routing balances performance and cost in hybrid systems by escalating selected queries from a lightweight model to a powerful but expensive one. Hidden-state probes provide an effe…
PreFlect: From Retrospective to Prospective Reflection in Large Language Model Agents
Hanyu Wang, Yuanpu Cao, Lu Lin +1
Advanced large language model agents typically adopt self-reflection for improving performance, where agents iteratively analyze past actions to correct errors. However, existing r…
Phi: Preference Hijacking in Multi-modal Large Language Models at Inference Time
Yifan Lan, Yuanpu Cao, Weitong Zhang +2
Recently, Multimodal Large Language Models (MLLMs) have gained significant attention across various domains. However, their widespread adoption has also raised serious safety conce…
CyGATE: Game-Theoretic Cyber Attack-Defense Engine for Patch Strategy Optimization
Yuning Jiang, Nay Oo, Qiaoran Meng +5
Modern cyber attacks unfold through multiple stages, requiring defenders to dynamically prioritize mitigations under uncertainty. While game-theoretic models capture attacker-defen…
Topological Structure Learning Should Be A Research Priority for LLM-Based Multi-Agent Systems
Jiaxi Yang, Mengqi Zhang, Yiqiao Jin +8
Large Language Model-based Multi-Agent Systems (MASs) have emerged as a powerful paradigm for tackling complex tasks through collaborative intelligence. However, the topology of th…
From Evaluation to Defense: Advancing Safety in Video Large Language Models
Yiwei Sun, Peiqi Jiang, Chuanbin Liu +3
While the safety risks of image-based large language models (Image LLMs) have been extensively studied, their video-based counterparts (Video LLMs) remain critically under-examined…
GuardDoor: Safeguarding Against Malicious Diffusion Editing via Protective Backdoors
Yaopei Zeng, Yuanpu Cao, Lu Lin
The growing accessibility of diffusion models has revolutionized image editing but also raised significant concerns about unauthorized modifications, such as misinformation and pla…
Understanding and Rectifying Safety Perception Distortion in VLMs
Xiaohan Zou, Jian Kang, George Kesidis +1
Recent studies reveal that vision-language models (VLMs) become more susceptible to harmful requests and jailbreak attacks after integrating the vision modality, exhibiting greater…
Adversarially Robust Industrial Anomaly Detection Through Diffusion Model
Yuanpu Cao, Lu Lin, Jinghui Chen
Deep learning-based industrial anomaly detection models have achieved remarkably high accuracy on commonly used benchmark datasets. However, the robustness of those models may not…
Personalized Steering of Large Language Models: Versatile Steering Vectors Through Bi-directional Preference Optimization
Yuanpu Cao, Tianrong Zhang, Bochuan Cao +4
Researchers have been studying approaches to steer the behavior of Large Language Models (LLMs) and build personalized LLMs tailored for various applications. While fine-tuning see…
How Chinese are Chinese Language Models? The Puzzling Lack of Language Policy in China's LLMs
Andrea W Wen-Yi, Unso Eun Seo Jo, Lu Jia Lin +1
Contemporary language models are increasingly multilingual, but Chinese LLM developers must navigate complex political and business considerations of language diversity. Language p…
WordGame: Efficient & Effective LLM Jailbreak via Simultaneous Obfuscation in Query and Response
Tianrong Zhang, Bochuan Cao, Yuanpu Cao +3
The recent breakthrough in large language models (LLMs) such as ChatGPT has revolutionized production processes at an unprecedented pace. Alongside this progress also comes mountin…
JoPA:Explaining Large Language Model's Generation via Joint Prompt Attribution
Yurui Chang, Bochuan Cao, Yujia Wang +2
Large Language Models (LLMs) have demonstrated impressive performances in complex text generation tasks. However, the contribution of the input prompt to the generated content stil…