5 papers
Hybrid Advantage Estimation with Unified Critic for VLM Agentic Reinforcement Learning
Wenxuan Zhang, Yuhui Wang, Donggang Jia +5
Large Vision-Language Models (VLMs) now act as agents in interactive environments, where success requires coherent reasoning and decision-making across turns. Although end-to-end t…
Scaling Agentic Reinforcement Learning for Tool-Integrated Reasoning in VLMs
Meng Lu, Ran Xu, Yi Fang +14
While recent vision-language models (VLMs) demonstrate strong image understanding, their ability to "think with images", i.e., to reason through multi-step visual interactions, rem…
Vgent: Graph-based Retrieval-Reasoning-Augmented Generation For Long Video Understanding
Xiaoqian Shen, Wenxuan Zhang, Jun Chen +1
Understanding and reasoning over long videos pose significant challenges for large video language models (LVLMs) due to the difficulty in processing intensive video tokens beyond c…
Query-based Knowledge Transfer for Heterogeneous Learning Environments
Norah Alballa, Wenxuan Zhang, Ziquan Liu +3
Decentralized collaborative learning under data heterogeneity and privacy constraints has rapidly advanced. However, existing solutions like federated learning, ensembles, and tran…
Bi-Factorial Preference Optimization: Balancing Safety-Helpfulness in Language Models
Wenxuan Zhang, Philip H. S. Torr, Mohamed Elhoseiny +1
Fine-tuning large language models (LLMs) on human preferences, typically through reinforcement learning from human feedback (RLHF), has proven successful in enhancing their capabil…