Datasets:

VideoMemBench
/

data

@@ -31,7 +31,7 @@ configs:
   <a href="https://videomembench.github.io/#results"><img src="https://img.shields.io/badge/%F0%9F%8F%86%20Leaderboard-Rank-e6b000?style=flat-square" alt="🏆 Leaderboard: Rank" height="26" /></a>
 </p>
-## Benchmark
 VideoMemBench evaluates **in-context video memory**: the ability to retrieve and reuse information established earlier in a multi-turn conversation about a video. Each sample pairs one video with an ordered dialogue, reference answers, and typed dependencies between turns.
@@ -40,7 +40,7 @@ VideoMemBench evaluates **in-context video memory**: the ability to retrieve and
 Dependencies are checked for necessity and non-leakage, and answers must be visually grounded. A planner, generator, and judger construct and check dialogues, followed by human expert review. See the [paper](https://arxiv.org/html/2610.40131v1) for construction and collection details.
-## Leaderboard
 <div style="overflow-x: auto;">
 <table style="display: table; width: 100%; min-width: 760px; font-size: 14px; color: #20202c; background-color: white;">
@@ -259,7 +259,7 @@ Dependencies are checked for necessity and non-leakage, and answers must be visu
 </table>
 </div>
-### Evaluation with fewer frames
 13 open-weight models evaluated with 64 or 32 fixed frames per video.
@@ -517,13 +517,13 @@ Dependencies are checked for necessity and non-leakage, and answers must be visu
 For download and evaluation instructions, see the [GitHub documentation](https://github.com/Oliiveralien/VideoMemBench#readme).
-## License and terms of use
 - Dataset annotations: [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/).
 - For non-commercial academic research and evaluation only. Not for model training.
 - Source videos are not covered by this license; their original rights and terms apply.
-## Citation
 ```bibtex
 @misc{hu2026videomembenchmllmsremembervideo,

   <a href="https://videomembench.github.io/#results"><img src="https://img.shields.io/badge/%F0%9F%8F%86%20Leaderboard-Rank-e6b000?style=flat-square" alt="🏆 Leaderboard: Rank" height="26" /></a>
 </p>
+## 🎬 Benchmark
 VideoMemBench evaluates **in-context video memory**: the ability to retrieve and reuse information established earlier in a multi-turn conversation about a video. Each sample pairs one video with an ordered dialogue, reference answers, and typed dependencies between turns.
 Dependencies are checked for necessity and non-leakage, and answers must be visually grounded. A planner, generator, and judger construct and check dialogues, followed by human expert review. See the [paper](https://arxiv.org/html/2610.40131v1) for construction and collection details.
+## 🏆 Leaderboard
 <div style="overflow-x: auto;">
 <table style="display: table; width: 100%; min-width: 760px; font-size: 14px; color: #20202c; background-color: white;">
 </table>
 </div>
+### 🎞️ Evaluation with fewer frames
 13 open-weight models evaluated with 64 or 32 fixed frames per video.
 For download and evaluation instructions, see the [GitHub documentation](https://github.com/Oliiveralien/VideoMemBench#readme).
+## 📜 License and terms of use
 - Dataset annotations: [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/).
 - For non-commercial academic research and evaluation only. Not for model training.
 - Source videos are not covered by this license; their original rights and terms apply.
+## 📚 Citation
 ```bibtex
 @misc{hu2026videomembenchmllmsremembervideo,