9 papers
Be Consistent! Enhancing Robust Visual Reasoning in LVLMs with Consistency Constraints
Liqiang Jing, Xiong Zhou, Siddharth Varia +3
While Large Vision-Language Models (LVLMs) exhibit strong perceptual capabilities, they remain vulnerable in visual reasoning tasks. Existing benchmarks largely focus on symbolic m…
CLUE: Non-parametric Verification from Experience via Hidden-State Clustering
Zhenwen Liang, Ruosen Li, Yujun Zhou +5
Assessing the quality of Large Language Model (LLM) outputs presents a critical challenge. Previous methods either rely on text-level information (e.g., reward models, majority vot…
Multimodal Reference Visual Grounding
Yangxiao Lu, Ruosen Li, Liqiang Jing +5
Visual grounding focuses on detecting objects from images based on language expressions. Recent Large Vision-Language Models (LVLMs) have significantly advanced visual grounding pe…
FG-PRM: Fine-grained Hallucination Detection and Mitigation in Language Model Mathematical Reasoning
Ruosen Li, Ziming Luo, Xinya Du
Hallucinations in large language models (LLMs) pose significant challenges in tasks requiring complex multi-step reasoning, such as mathematical problem-solving. Existing approache…
FIFA: Unified Faithfulness Evaluation Framework for Text-to-Video and Video-to-Text Generation
Liqiang Jing, Viet Lai, Seunghyun Yoon +2
Video Multimodal Large Language Models (VideoMLLMs) have achieved remarkable progress in both Video-to-Text and Text-to-Video tasks. However, they often suffer fro hallucinations,…
FIHA: Autonomous Hallucination Evaluation in Vision-Language Models with Davidson Scene Graphs
Bowen Yan, Zhengsong Zhang, Liqiang Jing +2
The rapid development of Large Vision-Language Models (LVLMs) often comes with widespread hallucination issues, making cost-effective and comprehensive assessments increasingly vit…