LRV-Instruction
Hallucination mitigation
A research project focused on mitigating hallucinations in large multi-modal models by improving instruction tuning through robust training methods.
[ICLR'24] Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
262 stars
11 watching
13 forks
Language: Python
last commit: over 2 years agochatgptevaluationevaluation-metricsfoundation-modelsgptgpt-4hallucinationiclriclr2024llamallavamultimodalobject-detectionprompt-engineeringvicunavisionvision-and-languagevqa
Related projects:
| Repository | Description | Stars |
|---|---|---|
 1zhou-wang/memvr | An implementation of a method to mitigate hallucinations in large language models using visual re-tracing | 28 |
 yuezih/less-is-more | Improving multimodal hallucination mitigation in EOS decision-making by selectively supervising training data | 39 |
 lalbj/pai | Improves the performance of large language models by intervening in their internal workings to reduce hallucinations | 83 |
 yuqifan1117/hallucidoctor | This project provides tools and frameworks to mitigate hallucinatory toxicity in visual instruction data, allowing researchers to fine-tune MLLM models on specific datasets. | 41 |
 x-plug/mplug-halowl | Evaluates and mitigates hallucinations in multimodal large language models | 82 |
 bradyfu/woodpecker | A method to correct hallucinations in multimodal large language models without requiring retraining | 617 |
 tianyi-lab/hallusionbench | An image-context reasoning benchmark designed to challenge large vision-language models and help improve their accuracy | 259 |
 yfzhang114/llava-align | Debiasing techniques to minimize hallucinations in large visual language models | 75 |
 yiyangzhou/lure | Analyzing and mitigating object hallucination in large vision-language models to improve their accuracy and reliability. | 136 |
 assafbk/mocha_code | A unified framework and benchmark for detecting and mitigating hallucinations in open-vocabulary image captioning models | 13 |
 billchan226/halc | An implementation of an object hallucination reduction method using a PyTorch framework and various decoding algorithms. | 72 |
 opendatalab/ha-dpo | A framework to improve large language model performance by mitigating hallucination effects through data and optimization techniques. | 73 |
 vectara/hallucination-leaderboard | Compares performance of large language models on generating coherent summaries from short documents | 1,281 |
 openmoss/halluqa | An evaluation framework for assessing the performance of large language models on question-answering tasks with hallucination detection | 111 |
| fuxiaoliu/mmc | Develops a large-scale dataset and benchmark for training multimodal chart understanding models using large language models. | 87 |