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Fix arXiv link and update citation details #2

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22 changes: 12 additions & 10 deletions README.md
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Expand Up @@ -2,7 +2,7 @@

<div align="center">

[![arXiv](https://img.shields.io/badge/arXiv-2024.XXXXX-b31b1b.svg?style=flat-square)](https://arxiv.org/abs/2024.XXXXX)
[![arXiv](https://img.shields.io/badge/arXiv-2025.03955-b31b1b.svg?style=flat-square)](https://arxiv.org/abs/2510.03955)
[![Hugging Face](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Models-blue?style=flat-square)](https://huggingface.co/time-warp)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg?style=flat-square)](https://opensource.org/licenses/MIT)

Expand All @@ -24,7 +24,7 @@ pip install -r requirements.txt
## 📦 Dataset Setup

### Option 1: Download Preprocessed Data
[![Hugging Face Dataset](https://img.shields.io/badge/%F0%9F%A4%97%20Dataset-TimeWarp-orange?style=flat-square)](https://huggingface.co/datasets/time-warp/timewarp-data)
[![Hugging Face Dataset](https://img.shields.io/badge/%F0%9F%A4%97%20Dataset-TimeWarp-orange?style=flat-square)](https://huggingface.co/datasets/time-warp/timewarp)

### Option 2: Generate from Scratch

Expand Down Expand Up @@ -64,14 +64,16 @@ TimeWarp/
If you find our work helpful, please consider citing:

```bibtex
Coming Soon
@misc{vani2025harnessingsyntheticpreferencedata,
title={Harnessing Synthetic Preference Data for Enhancing Temporal Understanding of Video-LLMs},
author={Sameep Vani and Shreyas Jena and Maitreya Patel and Chitta Baral and Somak Aditya and Yezhou Yang},
year={2025},
eprint={2510.03955},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2510.03955},
}
```
<!-- @article{timewarp2024,
title={Harnessing Synthetic Preference Data for Enhancing Temporal Understanding of Video-LLMs},
author={Your Name et al.},
journal={arXiv preprint arXiv:2024.XXXXX},
year={2024}
} -->

## 🤝 Contributing

Expand All @@ -83,4 +85,4 @@ This project is licensed under the MIT License - see the [LICENSE](LICENSE) file

## 🙏 Acknowledgments

We thank the authors of LLaVA-Hound, Video-LLaMA3, and FineVideo for their foundational work.
We thank the authors of LLaVA-Hound, Video-LLaMA3, and FineVideo for their foundational work.