HaELM
Hallucination detector
A framework for detecting hallucinations in large language models
An automatic MLLM hallucination detection framework
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Language: Python
last commit: almost 3 years agoRelated projects:
| Repository | Description | Stars |
|---|---|---|
 openkg-org/easydetect | A framework to detect and mitigate hallucinations in multimodal large language models | 48 |
 openmoss/halluqa | An evaluation framework for assessing the performance of large language models on question-answering tasks with hallucination detection | 111 |
 amazon-science/refchecker | Automates fine-grained hallucination detection in large language model outputs | 325 |
| junyangwang0410/amber | An LLM-free benchmark suite for evaluating MLLMs' hallucination capabilities in various tasks and dimensions | 98 |
 x-plug/mplug-halowl | Evaluates and mitigates hallucinations in multimodal large language models | 82 |
 1zhou-wang/memvr | An implementation of a method to mitigate hallucinations in large language models using visual re-tracing | 28 |
 bradyfu/woodpecker | A method to correct hallucinations in multimodal large language models without requiring retraining | 617 |
 billchan226/halc | An implementation of an object hallucination reduction method using a PyTorch framework and various decoding algorithms. | 72 |
 assafbk/mocha_code | A unified framework and benchmark for detecting and mitigating hallucinations in open-vocabulary image captioning models | 13 |
 rucaibox/pope | An evaluation framework for detecting object hallucinations in vision-language models | 187 |
 chanyn/hkrm | Develops a deep learning model for large-scale object detection that leverages hybrid knowledge and routing mechanisms. | 105 |
 bcdnlp/faithscore | Evaluates answers generated by large vision-language models to assess hallucinations | 27 |
 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 |
 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 |
 tianyi-lab/hallusionbench | An image-context reasoning benchmark designed to challenge large vision-language models and help improve their accuracy | 259 |