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cs.CV2026

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…

cs.CV2025

Dr.V: A Hierarchical Perception-Temporal-Cognition Framework to Diagnose Video Hallucination by Fine-grained Spatial-Temporal Grounding

Meng Luo, Shengqiong Wu, Liqiang Jing +12

Recent advancements in large video models (LVMs) have significantly enhance video understanding. However, these models continue to suffer from hallucinations, producing content tha…

cs.CV2025

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,…

cs.CV2025

A Comprehensive Analysis for Visual Object Hallucination in Large Vision-Language Models

Liqiang Jing, Guiming Hardy Chen, Ehsan Aghazadeh +2

Large Vision-Language Models (LVLMs) demonstrate remarkable capabilities in multimodal tasks, but visual object hallucination remains a persistent issue. It refers to scenarios whe…

cs.CV2025

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…