mPLUG-HalOwl: Multimodal Hallucination Evaluation and Mitigating

Works

• AMBER --- An Automated Multi-dimensional Benchmark for Multi-modal Hallucination Evaluation
• HACL --- Hallucination Augmented Contrastive Learning for Multimodal Large Language Model.
• HaELM --- An automatic MLLM hallucination detection framework.

License

The content of this project itself is licensed under LICENSE.

Citation

If you found our works useful, consider giving this repository a star and citing our paper as followed:

@article{wang2023llm,
  title={An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation},
  author={Wang, Junyang and Wang, Yuhang and Xu, Guohai and Zhang, Jing and Gu, Yukai and Jia, Haitao and Yan, Ming and Zhang, Ji and Sang, Jitao},
  journal={arXiv preprint arXiv:2311.07397},
  year={2023}
}

@misc{jiang2023hallucination,
      title={Hallucination Augmented Contrastive Learning for Multimodal Large Language Model}, 
      author={Chaoya Jiang and Haiyang Xu and Mengfan Dong and Jiaxing Chen and Wei Ye and Ming Yan and Qinghao Ye and Ji Zhang and Fei Huang and Shikun Zhang},
      year={2023},
      eprint={2312.06968},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

@article{wang2023evaluation,
  title={Evaluation and Analysis of Hallucination in Large Vision-Language Models},
  author={Wang, Junyang and Zhou, Yiyang and Xu, Guohai and Shi, Pengcheng and Zhao, Chenlin and Xu, Haiyang and Ye, Qinghao and Yan, Ming and Zhang, Ji and Zhu, Jihua and others},
  journal={arXiv preprint arXiv:2308.15126},
  year={2023}
}