11 papers
Reasoning with Memory: A Temporal Granularity-Adaptive Framework for Training-Free Long Video Understanding
Linghao Meng, Qiankun Li, Junyuan Mao +7
While Multimodal Large Language Models (MLLMs) demonstrate superior generalization in fundamental video tasks, restricted context windows limit their long video understanding. To a…
Synergistic Perception-Reasoning Governance: Grounding Medical MLLMs with Verifiable Anatomical Evidence
Rui Hao, Qiankun Li, Junyuan Mao +4
Multimodal large language models (MLLMs) show strong promise for clinical VQA and radiology report generation, yet inference-time hallucinations still undermine trustworthy use: mo…
Granulon: Awakening Pixel-Level Visual Encoders with Adaptive Multi-Granularity Semantics for MLLM
Junyuan Mao, Qiankun Li, Linghao Meng +5
Recent advances in multimodal large language models largely rely on CLIP-based visual encoders, which emphasize global semantic alignment but struggle with fine-grained visual unde…
Multi-scale Temporal Prediction via Incremental Generation and Multi-agent Collaboration
Zhitao Zeng, Guojian Yuan, Junyuan Mao +3
Accurate temporal prediction is the bridge between comprehensive scene understanding and embodied artificial intelligence. However, predicting multiple fine-grained states of a sce…
AgentSafe: Safeguarding Large Language Model-based Multi-agent Systems via Hierarchical Data Management
Junyuan Mao, Fanci Meng, Yifan Duan +6
Large Language Model based multi-agent systems are revolutionizing autonomous communication and collaboration, yet they remain vulnerable to security threats like unauthorized acce…
A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment
Kun Wang, Guibin Zhang, Zhenhong Zhou +100
The remarkable success of Large Language Models (LLMs) has illuminated a promising pathway toward achieving Artificial General Intelligence for both academic and industrial communi…