activity
20242026
collaborators

8 papers

cs.LG2026

Understanding and Preventing Entropy Collapse in RLVR with On-Policy Entropy Flow Optimization

Huimin Xu, Shuai Zhao, Xiaobao Wu +1

Reinforcement learning with verifiable rewards (RLVR) has become an effective paradigm for improving the reasoning ability of large language models. However, widely used RLVR algor…

cs.CV2026

EduStory: A Unified Framework for Pedagogically-Consistent Multi-Shot STEM Instructional Video Generation

Xinyi Wu, Jayant Teotia, Shuai Zhao +1

Long-horizon video generation has advanced in visual quality, yet existing methods still struggle to maintain knowledge consistency and coherent pedagogical narratives across multi…

cs.DB2025

From Stimuli to Minds: Enhancing Psychological Reasoning in LLMs via Bilateral Reinforcement Learning

Yichao Feng, Haoran Luo, Lang Feng +2

Large Language Models show promise in emotion understanding, social reasoning, and empathy, yet they struggle with psychologically grounded tasks that require inferring implicit me…

cs.CL2025

Aspect-Based Summarization with Self-Aspect Retrieval Enhanced Generation

Yichao Feng, Shuai Zhao, Yueqiu Li +3

Aspect-based summarization aims to generate summaries tailored to specific aspects, addressing the resource constraints and limited generalizability of traditional summarization ap…

cs.CV2025

CutPaste&Find: Efficient Multimodal Hallucination Detector with Visual-aid Knowledge Base

Cong-Duy Nguyen, Xiaobao Wu, Duc Anh Vu +3

Large Vision-Language Models (LVLMs) have demonstrated impressive multimodal reasoning capabilities, but they remain susceptible to hallucination, particularly object hallucination…

cs.CV2025

Enhancing Multimodal Entity Linking with Jaccard Distance-based Conditional Contrastive Learning and Contextual Visual Augmentation

Cong-Duy Nguyen, Xiaobao Wu, Thong Nguyen +5

Previous research on multimodal entity linking (MEL) has primarily employed contrastive learning as the primary objective. However, using the rest of the batch as negative samples…