Update model card

README.md

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-license: bsd-3-clause
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+---
+license: bsd-3-clause
+---
+
+# E.T. Chat
+
+[arXiv](https://arxiv.org/abs/2409.18111) | [Project Page](https://polyu-chenlab.github.io/etbench) | [GitHub](https://github.com/PolyU-ChenLab/ETBench)
+
+E.T. Chat is a novel time-sensitive Video-LLM that reformulates timestamp prediction as an embedding matching problem, serving as a strong baseline on E.T. Bench. E.T. Chat consists of a visual encoder, a frame compressor, and a LLM. A special token \<vid\> is introduced to trigger frame embedding matching for timestamp prediction.
+
+## 🔖 Model Details
+
+### Model Description
+
+- **Developed by:** Ye Liu
+- **Model type:** Multi-modal Large Language Model
+- **Language(s):** English
+- **License:** BSD-3-Clause
+
+### Training Data
+
+The stage-2 checkpoint of E.T. Chat was trained from [VideoChatGPT](https://mbzuaiac-my.sharepoint.com/:f:/g/personal/hanoona_bangalath_mbzuai_ac_ae/EnLRDehrr8lGqHpC5w1zZ9QBnsiVffYy5vCv8Hl14deRcg?e=Ul5DUE) and [LLaVA-1.5-Instruct](https://github.com/haotian-liu/LLaVA?tab=readme-ov-file#visual-instruction-tuning) datasets.
+
+### More Details
+
+Please refer to our [GitHub Repository](https://github.com/PolyU-ChenLab/ETBench) for more details about this model.
+
+## 📖 Citation
+
+Please kindly cite our paper if you find this project helpful.
+
+```
+@inproceedings{liu2024etbench,
+  title={E.T. Bench: Towards Open-Ended Event-Level Video-Language Understanding},
+  author={Liu, Ye and Ma, Zongyang and Qi, Zhongang and Wu, Yang and Chen, Chang Wen and Shan, Ying},
+  booktitle={Neural Information Processing Systems (NeurIPS)},
+  year={2024}
+}
+```