1 citations · 2 across the 8 of their papers we have counts for
9 papers
SCAD: Structured Credit Assignment and Distillation for Long-Horizon Agents
Shangyang Wu, Shuai Zhao, Ziyue Zhu +3
Training long-horizon agents to solve complex tasks requires effective supervision over extended interaction sequences. However, sparse terminal rewards obscure intermediate contri…
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…
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…
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…
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…
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…
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…
AntiLeakBench: Preventing Data Contamination by Automatically Constructing Benchmarks with Updated Real-World Knowledge
Xiaobao Wu, Liangming Pan, Yuxi Xie +7
Data contamination hinders fair LLM evaluation by introducing test data into newer models' training sets. Existing studies solve this challenge by updating benchmarks with newly co…
Unlearning Backdoor Attacks for LLMs with Weak-to-Strong Knowledge Distillation
Shuai Zhao, Xiaobao Wu, Cong-Duy Nguyen +4
Parameter-efficient fine-tuning (PEFT) can bridge the gap between large language models (LLMs) and downstream tasks. However, PEFT has been proven vulnerable to malicious attacks.…