Simplify dataset card and add paper, project, code, and citation

README.md

@@ -27,24 +27,7 @@ by remembering what earlier turns established. Each dialogue is grounded in one
 refers back to earlier turns either through a scene or entity they established (episodic dependency) or
 through their answers (answer dependency).
 
-## Statistics
-
-| | |
-|---|---|
-| Videos / dialogues | 326 |
-| Turns | 2,476 (open-ended 1,709, multiple-choice 603, true/false 164) |
-| Independent / dependent turns | 1,089 / 1,387 |
-| Typed dependencies | 1,794 (episodic 1,200, answer 594) |
-| Turns with multiple parents | 348 (two parents 289, three parents 59) |
-| Turns per dialogue | 4 to 21 (mean 7.6) |
-| Total video duration | about 154 hours (mean 28.4 minutes, longest 23.47 hours) |
-
-## Files
-
-```
-annotations.jsonl                                  one dialogue per line
-videos/videomembench-1.mp4 ... videomembench-326.mp4
-```
+[Paper](https://arxiv.org/abs/2610.40131v1) · [Project](https://videomembench.github.io) · [GitHub](https://github.com/Oliiveralien/VideoMemBench)
 
 ## Data format
 
@@ -71,13 +54,6 @@ videos/videomembench-1.mp4 ... videomembench-326.mp4
 An `answer` dependency means the turn needs the parent turn's correct answer. An `episodic` dependency
 means the turn returns to a scene or entity established in the parent turn.
 
-## Evaluation
-
-Each dialogue is replayed as one conversation. 128 frames are sampled uniformly, resized to at most 512 px
-on the longer side and sent once in the first user message; the model's own earlier answers stay in the
-history. Multiple-choice and true/false turns are scored by rule, and open-ended turns by an LLM judge
-against the reference answer. Evaluation code: https://anonymous.4open.science/r/VideoMemBench-4C21
-
 ## License and terms of use
 
 - The annotations (questions, options, answers and dependency labels) are released under
@@ -93,11 +69,16 @@ against the reference answer. Evaluation code: https://anonymous.4open.science/r
 - If you hold rights to a video, or a video shows you and you want it removed, please open a discussion in
   the Community tab of this repository and we will remove it promptly.
 
-## Privacy
-
-Videos taken from existing datasets keep any anonymization applied by their original creators, such as
-face blurring.
-
 ## Citation
 
-Citation information will be added after the review period.
+```bibtex
+@misc{hu2026videomembenchmllmsremembervideo,
+  title={VideoMemBench: How Well Do MLLMs Remember in Video Conversations?},
+  author={Zhengdong Hu and Chao Wang and Kaituo Feng and Huanjin Yao and Mingfei Lu and Hehe Fan and Yi Yang},
+  year={2026},
+  eprint={2610.40131},
+  archivePrefix={arXiv},
+  primaryClass={cs.CV},
+  url={https://arxiv.org/abs/2610.40131},
+}
+```