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