Update dataset card

README.md

@@ -4,13 +4,11 @@ license: cc-by-nc-sa-4.0
 
 # E.T. Bench
 
-<p align="center">
-  <img width="700" src="https://github.com/PolyU-ChenLab/ETBench/blob/main/.github/benchmark.jpg">
-</p>
+[arXiv](https://arxiv.org/abs/2409.18111) | [Project Page](https://polyu-chenlab.github.io/etbench) | [GitHub](https://github.com/PolyU-ChenLab/ETBench)
 
 E.T. Bench is a large-scale and high-quality benchmark for open-ended event-level video understanding. Categorized within a 3-level task taxonomy, it encompasses 7.3K samples under 12 tasks with 7K videos (251.4h total length) under 8 domains, providing comprehensive evaluations on 4 essential capabilities for time-sensitive video understanding.
 
-## 📚 Data Preparation
+## 📦 Data Preparation
 
 You may download the evaluation kit for E.T. Bench using the following command.
 
@@ -120,10 +118,10 @@ The evaluation log and computed metrics will be saved in `metrics.log` and `metr
 Please kindly cite our paper if you find this project helpful.
 
 ```
-@article{liu2024etbench,
+@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},
-  journal={Tech Report},
+  booktitle={Neural Information Processing Systems (NeurIPS)},
   year={2024}
 }
-```
+```