Haigang Zhang — accepted AI-conference papers

2025

Seeing More, Saying More: Lightweight Language Experts are Dynamic Video Token Compressors

Xiangchen Wang, Jinrui Zhang, Teng Wang, Haigang Zhang, Feng Zheng

EMNLP 2025

Recent advancements in large video-language models have revolutionized video understanding tasks. However, their efficiency is significantly constrained by processing high volumes of visual tokens. Existing token compression strategies apply a fixed compression ratio, ignoring the variability in sem

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2024

Reflective Instruction Tuning: Mitigating Hallucinations in Large Vision-Language Models

Jinrui Zhang, Teng Wang, Haigang Zhang, Ping Lu, Feng Zheng*

ECCV 2024poster

"Large vision-language models (LVLMs) have shown promising performance on a variety of vision-language tasks. However, they remain susceptible to hallucinations, generating outputs misaligned with visual content or instructions. While various mitigation strategies have been proposed, they often negl…

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