10 papers
ProV-Mem: Proactive Memory for Streaming Video Question Answering
Bingbing Wang, Jing Li, Han Gao +3
Proactive streaming video question answering requires a model to continuously monitor an incoming stream and autonomously decide when to speak, what to say, and whether to emit a r…
All-in-One Memory: Process-Rewarded Reinforcement Learning for Memory Agents
Bingbing Wang, Jingjie Lin, Weiming Qiao +2
Large language models increasingly rely on external memory to answer queries grounded in long-horizon histories such as multi-session dialogues and lengthy documents. However, exis…
BAIT: Boundary-Guided Disclosure Escalation LLM Jailbreaking via Self-Conditioned Reasoning
Xuan Luo, Yue Wang, Geng Tu +2
In this work, we propose BAIT (Boundary-Aware Iterative Trap), a three-step jailbreak framework that elicits malicious information through internal disclosure by target large langu…
Mitigating Provenance-Role Collapse in Long-Term Agents via Typed Memory Representation
Zhengda Jin, Bingbing Wang, Jing Li +2
Long-term memory is essential for persistent LLM agents, yet prevailing architectures store historical interactions as unstructured, flat text. This unconstrained storage induces p…
Speech-Omni-Lite: Portable Speech Interfaces for Vision-Language Models
Dehua Tao, Xuan Luo, Daxin Tan +5
While large-scale omni-models have demonstrated impressive capabilities across various modalities, their strong performance heavily relies on massive multimodal data and incurs sub…
Proactive Memory for Ad-Hoc Recall over Streaming Dialogues
Bingbing Wang, Jing Li, Ruifeng Xu
Real-world dialogue usually unfolds as an infinite stream. It thus requires bounded-state memory mechanisms to operate within an infinite horizon. However, existing read-then-think…
CoreEval: Automatically Building Contamination-Resilient Datasets with Real-World Knowledge toward Reliable LLM Evaluation
Jingqian Zhao, Bingbing Wang, Geng Tu +5
Data contamination poses a significant challenge to the fairness of LLM evaluations in natural language processing tasks by inadvertently exposing models to test data during traini…
PRISM of Opinions: A Persona-Reasoned Multimodal Framework for User-centric Conversational Stance Detection
Bingbing Wang, Zhixin Bai, Zhengda Jin +6
The rapid proliferation of multimodal social media content has driven research in Multimodal Conversational Stance Detection (MCSD), which aims to interpret users' attitudes toward…
MIND Your Reasoning: A Meta-Cognitive Intuitive-Reflective Network for Dual-Reasoning in Multimodal Stance Detection
Bingbing Wang, Zhengda Jin, Bin Liang +4
Multimodal Stance Detection (MSD) is a crucial task for understanding public opinion on social media. Existing methods predominantly operate by learning to fuse modalities. They la…
A Simple and Efficient Jailbreak Method Exploiting LLMs' Helpfulness
Xuan Luo, Yue Wang, Zefeng He +3
This study reveals a critical safety blind spot in modern LLMs: learning-style queries, which closely resemble ordinary educational questions, can reliably elicit harmful responses…