MemVR
by 1zhou-Wang
Official implementation of paper 'Look Twice Before You Answer: Memory-Space Visual Retracing for Hallucination Mitigation in Multimodal Large Language Models'.
AI summary
Hallucination fixer
An implementation of a method to mitigate hallucinations in large language models using visual re-tracing
- stars
- 28
- forks
- 2
- watching
- 3
Similar projects
Found by comparing what the projects do, not just their names.
Hallucination corrector
A method to correct hallucinations in multimodal large language models without requiring retraining
Hallucination fixer
Improves the performance of large language models by intervening in their internal workings to reduce hallucinations
Hallucination fixer
A framework to improve large language model performance by mitigating hallucination effects through data and optimization techniques.
Model validator
Analyzing and mitigating object hallucination in large vision-language models to improve their accuracy and reliability.
Hallucination mitigation
A research project focused on mitigating hallucinations in large multi-modal models by improving instruction tuning through robust training methods.
Hallucination detector
A framework for detecting hallucinations in large language models
Hallucination tester
Evaluates and mitigates hallucinations in multimodal large language models
Benchmark
An image-context reasoning benchmark designed to challenge large vision-language models and help improve their accuracy
Hallucination Detector
Automates fine-grained hallucination detection in large language model outputs
Data processing framework
This project provides tools and frameworks to mitigate hallucinatory toxicity in visual instruction data, allowing researchers to fine-tune MLLM models on specific datasets.
Object hallucination reducer
An implementation of an object hallucination reduction method using a PyTorch framework and various decoding algorithms.
Model debiasing
Debiasing techniques to minimize hallucinations in large visual language models
Object detection method
An approach to reduce object hallucinations in large vision-language models by contrasting output distributions derived from original and distorted visual inputs
Hallucination detection and mitigation
A unified framework and benchmark for detecting and mitigating hallucinations in open-vocabulary image captioning models
Hallucination detector
An evaluation framework for assessing the performance of large language models on question-answering tasks with hallucination detection
