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--- |
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license: apache-2.0 |
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datasets: |
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- helehan/topic-overwrite |
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language: |
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- en |
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--- |
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# Model Card for Model ID |
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[GitHub](https://github.com/topic-overwrite/topic-level-overwrite/tree/main) | [Paper](https://arxiv.org/abs/2411.17265) |
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## Model Details |
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The model, trained using the RLHF/RLAIF methods proposed in the [TPO paper](https://arxiv.org/abs/2411.17265) by llava, has enhanced trustworthiness and reduced hallucinations. |
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## Model Description |
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- **Trained from model:** [llava-v1.5-7B](https://huggingface.co/liuhaotian/llava-v1.5-7b) |
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- **Trained on data:** [TPO-Dataset](https://huggingface.co/datasets/helehan/topic-overwrite) |
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## Usage |
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Please look at [GitHub](https://github.com/topic-overwrite/topic-level-overwrite/tree/main) for more details about usage. |
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## Citation |
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```bibtex |
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@article{he2024topic, |
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title={A Topic-level Self-Correctional Approach to Mitigate Hallucinations in MLLMs}, |
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author={He, Lehan and Chen, Zeren and Shi, Zhelun and Yu, Tianyu and Shao, Jing and Sheng, Lu}, |
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journal={arXiv preprint arXiv:2411.17265}, |
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year={2024} |
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} |
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``` |
