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FineGen: A VLM-based Multi-Agent Framework for Fine-Grained Image-Text Dataset Construction
Chang Kong, Yuebing Li, Peng Mo +2
The scarcity of hard negative samples in current vision-language datasets significantly hinders fine-grained perception. To address this, we propose FineGen, a VLM-based Multi-Agen…
UniPCB: A Unified Vision-Language Benchmark for Open-Ended PCB Quality Inspection
Fuxiang Sun, Xi Jiang, Jiansheng Wu +3
Multimodal Large Language Models (MLLMs) show promise for general industrial quality inspection, but fall short in complex scenarios, such as Printed Circuit Board (PCB) inspection…
Seeing More, Saying More: Lightweight Language Experts are Dynamic Video Token Compressors
Xiangchen Wang, Jinrui Zhang, Teng Wang +2
Recent advancements in large video-language models have revolutionized video understanding tasks. However, their efficiency is significantly constrained by processing high volumes…
Reflective Instruction Tuning: Mitigating Hallucinations in Large Vision-Language Models
Jinrui Zhang, Teng Wang, Haigang Zhang +2
Large vision-language models (LVLMs) have shown promising performance on a variety of vision-language tasks. However, they remain susceptible to hallucinations, generating outputs…