8 papers
Deep Research Brings Deeper Harm
Shuo Chen, Zonggen Li, Zhen Han +7
Deep Research (DR) agents built on Large Language Models (LLMs) can perform complex, multi-step research by decomposing tasks, retrieving online information, and synthesizing detai…
Bag of Tricks for Subverting Reasoning-based Safety Guardrails
Shuo Chen, Zhen Han, Haokun Chen +6
Recent reasoning-based safety guardrails for Large Reasoning Models (LRMs), such as deliberative alignment, have shown strong defense against jailbreak attacks. By leveraging LRMs'…
Can an Individual Manipulate the Collective Decisions of Multi-Agents?
Fengyuan Liu, Rui Zhao, Shuo Chen +4
Individual Large Language Models (LLMs) have demonstrated significant capabilities across various domains, such as healthcare and law. Recent studies also show that coordinated mul…
METok: Multi-Stage Event-based Token Compression for Efficient Long Video Understanding
Mengyue Wang, Shuo Chen, Kristian Kersting +2
Recent advances in Video Large Language Models (VLLMs) have significantly enhanced their ability to understand video content. Nonetheless, processing long videos remains challengin…
True Multimodal In-Context Learning Needs Attention to the Visual Context
Shuo Chen, Jianzhe Liu, Zhen Han +5
Multimodal Large Language Models (MLLMs), built on powerful language backbones, have enabled Multimodal In-Context Learning (MICL)-adapting to new tasks from a few multimodal demon…
Parameter-Efficient Routed Fine-Tuning: Mixture-of-Experts Demands Mixture of Adaptation Modules
Yilun Liu, Yunpu Ma, Yuetian Lu +3
Mixture-of-Experts (MoE) benefits from a dynamic routing mechanism among their specialized experts, which existing Parameter- Efficient Fine-Tuning (PEFT) strategies fail to levera…