Update README.md

README.md

@@ -36,4 +36,48 @@ configs:
     path: data/train-*
 ---
 
-This is the preview version of RIVER Bench. Only 20% of the annotations are visible.
+<div align="center">
+
+<h2>
+    <a href="https://arxiv.org/abs/2603.03985">[ICLR 2026] RIVER: A Real-Time Interaction Benchmark for Video LLMs</a>
+</h2>
+
+<img src="assets/RIVER logo.png" width="80" alt="RIVER logo">
+
+[Yansong Shi<sup>*</sup>](https://scholar.google.com/citations?user=R7J57vQAAAAJ), 
+[Qingsong Zhao<sup>*</sup>](https://scholar.google.com/citations?user=ux-dlywAAAAJ), 
+[Tianxiang Jiang<sup>*</sup>](https://github.com/Arsiuuu), 
+[Xiangyu Zeng](https://scholar.google.com/citations?user=jS13DXkAAAAJ&hl), 
+[Yi Wang](https://scholar.google.com/citations?user=Xm2M8UwAAAAJ), 
+[Limin Wang<sup>†</sup>](https://scholar.google.com/citations?user=HEuN8PcAAAAJ)
+
+</div>
+
+## Introduction
+This project introduces **RIVER Bench**, the first benchmark designed to evaluate the real-time interactive capabilities of Video Large Language Models through streaming video perception, featuring novel tasks for memory, live-perception, and proactive response.
+
+![RIVER](assets/river.jpg)
+
+## Dataset Preparation
+|Dataset       |URL|
+|--------------|---|
+|LongVideoBench|https://github.com/longvideobench/LongVideoBench|
+|Vript-RR      |https://github.com/mutonix/Vript|
+|LVBench       |https://github.com/zai-org/LVBench|
+|Ego4D         |https://github.com/facebookresearch/Ego4d|
+|QVHighlights  |https://github.com/jayleicn/moment_detr|
+
+## Citation
+
+If you find this project useful in your research, please consider cite:
+```BibTeX
+@misc{shi2026riverrealtimeinteractionbenchmark,
+      title={RIVER: A Real-Time Interaction Benchmark for Video LLMs}, 
+      author={Yansong Shi and Qingsong Zhao and Tianxiang Jiang and Xiangyu Zeng and Yi Wang and Limin Wang},
+      year={2026},
+      eprint={2603.03985},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2603.03985}, 
+}
+```