LLaVA-Align
Model debiasing
Debiasing techniques to minimize hallucinations in large visual language models
This is the official repo for Debiasing Large Visual Language Models, including a Post-Hoc debias method and Visual Debias Decoding strategy.
75 stars
2 watching
2 forks
Language: Python
last commit: 10 months ago debiasinghallucinationlarge-vision-language-models
Related projects:
| Repository | Description | Stars |
|---|---|---|
 bradyfu/woodpecker | A method to correct hallucinations in multimodal large language models without requiring retraining | 617 |
 yiyangzhou/lure | Analyzing and mitigating object hallucination in large vision-language models to improve their accuracy and reliability. | 136 |
 lalbj/pai | Improves the performance of large language models by intervening in their internal workings to reduce hallucinations | 83 |
 tianyi-lab/hallusionbench | An image-context reasoning benchmark designed to challenge large vision-language models and help improve their accuracy | 259 |
| yfzhang114/slime | Develops large multimodal models for high-resolution understanding and analysis of text, images, and other data types. | 143 |
 damo-nlp-sg/vcd | An approach to reduce object hallucinations in large vision-language models by contrasting output distributions derived from original and distorted visual inputs | 222 |
 pku-yuangroup/moe-llava | A large vision-language model using a mixture-of-experts architecture to improve performance on multi-modal learning tasks | 2,023 |
 alibaba/conv-llava | This project presents an optimization technique for large-scale image models to reduce computational requirements while maintaining performance. | 106 |
 x-plug/mplug-halowl | Evaluates and mitigates hallucinations in multimodal large language models | 82 |
 amazon-science/refchecker | Automates fine-grained hallucination detection in large language model outputs | 325 |
 fuxiaoliu/lrv-instruction | A research project focused on mitigating hallucinations in large multi-modal models by improving instruction tuning through robust training methods. | 262 |
 hdcvlab/deblurring-by-realistic-blurring | A Python implementation of a deblurring model using realistic blurring techniques. | 63 |
 hyeongseokson1/kpac | An implementation of a deep learning model for deblurring images affected by defocus. | 58 |
 yuezih/less-is-more | Improving multimodal hallucination mitigation in EOS decision-making by selectively supervising training data | 39 |
 wisconsinaivision/vip-llava | A system designed to enable large multimodal models to understand arbitrary visual prompts | 302 |