5 papers · 1 filter
NoLan: Mitigating Object Hallucinations in Large Vision-Language Models via Dynamic Suppression of Language Priors
Lingfeng Ren, Weihao Yu, Runpeng Yu +1
Object hallucination is a critical issue in Large Vision-Language Models (LVLMs), where outputs include objects that do not appear in the input image. A natural question arises fro…
Top-Down Compression: Revisit Efficient Vision Token Projection for Visual Instruction Tuning
Bonan li, Zicheng Zhang, Songhua Liu +2
Visual instruction tuning aims to enable large language models to comprehend the visual world, with a pivotal challenge lying in establishing an effective vision-to-language projec…
MM-Vet v2: A Challenging Benchmark to Evaluate Large Multimodal Models for Integrated Capabilities
Weihao Yu, Zhengyuan Yang, Lingfeng Ren +7
MM-Vet, with open-ended vision-language questions targeting at evaluating integrated capabilities, has become one of the most popular benchmarks for large multimodal model evaluati…
LinFusion: 1 GPU, 1 Minute, 16K Image
Songhua Liu, Weihao Yu, Zhenxiong Tan +1
Modern diffusion models, particularly those utilizing a Transformer-based UNet for denoising, rely heavily on self-attention operations to manage complex spatial relationships, thu…
Attention Prompting on Image for Large Vision-Language Models
Runpeng Yu, Weihao Yu, Xinchao Wang
Compared with Large Language Models (LLMs), Large Vision-Language Models (LVLMs) can also accept images as input, thus showcasing more interesting emergent capabilities and demonst…