collaborators

10 papers

cs.CV2026

VKnowU: Evaluating Visual Knowledge Understanding in Multimodal LLMs

Tianxiang Jiang, Sheng Xia, Yicheng Xu +5

While Multimodal Large Language Models (MLLMs) have become adept at recognizing objects, they often lack the intuitive, human-like understanding of the world's underlying physical…

cs.CV2026

InternVideo3: Agentify Foundation Models with Multimodal Contextual Reasoning

Ziang Yan, Sheng Xia, Jiashuo Yu +10

Recent progress in foundation models has shifted toward agentic behavior involving multi-step reasoning and tool use. However, open-source efforts largely focus on text-dominant se…

cs.AI2026

C-MIG: Multi-view Information Gain-based Retrieval-Augmented Generation for Clinical Diagnosis Reasoning

Yuwei Miao, Gen Li, Yunsheng Zeng +8

Retrieval-augmented generation combined with reinforcement learning has shown promise for grounding large language models in trustworthy medical evidence. However, existing methods…

cs.AI2026

EAPO: Entropy-Driven Adaptive Positive-Negative Sample Weighting for Policy Optimization in Open-Ended QA

Yunsheng Zeng, Gen Li, Yuwei Miao +8

Large Reasoning Models are typically trained via reinforcement learning from verifiable rewards (RLVR). However, existing approaches adopt fixed weights for positive and negative s…

cs.CV2026

Learning Goal-Oriented Vision-and-Language Navigation with Self-Improving Demonstrations at Scale

Songze Li, Zun Wang, Gengze Zhou +8

Goal-oriented vision-language navigation requires robust exploration capabilities for agents to navigate to specified goals in unknown environments without step-by-step instruction…

cs.CV2025

VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning

Xinhao Li, Ziang Yan, Desen Meng +7

Reinforcement Learning (RL) benefits Large Language Models (LLMs) for complex reasoning. Inspired by this, we explore integrating spatio-temporal specific rewards into Multimodal L…