| --- |
| license: cc-by-nc-4.0 |
| language: |
| - en |
| task_categories: |
| - question-answering |
| - visual-question-answering |
| task_ids: |
| - multiple-choice-qa |
| pretty_name: EgoMemReason |
| size_categories: |
| - n<1K |
| tags: |
| - egocentric-video |
| - long-video-understanding |
| - memory |
| - multimodal |
| - benchmark |
| - video-qa |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: annotations_public.jsonl |
| --- |
| |
| # EgoMemReason |
|
|
| **A Memory-driven Reasoning Benchmark for Long-Horizon Egocentric Video Understanding.** |
|
|
| 500 multiple-choice questions over **week-long egocentric video** (built on [EgoLife](https://egolife-ai.github.io/)) that evaluate three complementary kinds of memory: |
|
|
| - **Entity memory** — track how object states evolve across days |
| - **Event memory** — recall and order activities separated by hours or days |
| - **Behavior memory** — abstract recurring patterns from sparse, repeated observations |
|
|
| Average **5.1 evidence segments per question** and **25.9 hours of memory backtracking** — 2× both metrics over the strongest prior week-long benchmark. |
|
|
| ## Links |
|
|
| - 🧠 **Leaderboard (HF Space):** <https://huggingface.co/spaces/Ted412/EgoMemReason> |
| - 💻 **Code & reference eval scripts:** <https://github.com/Ziyang412/EgoMemReason> |
| - 🌐 **Project page:** <https://egomemreason.github.io/> |
| - 🎬 **EgoLife video frames (separate license):** <https://egolife-ai.github.io/> |
| - 📄 **Paper:** <https://arxiv.org/abs/2605.09874> |
|
|
| ## Composition |
|
|
| | Memory type | Capability (`query_type`) | # Qs | |
| |---|---|---:| |
| | Entity | Cumulative State Tracking | 100 | |
| | Entity | Temporal Counting | 100 | |
| | Event | Event Ordering | 100 | |
| | Event | Event Linking | 100 | |
| | Behavior | Spatial Preference | 50 | |
| | Behavior | Activity Pattern | 50 | |
| | **Total** | | **500** | |
|
|
| ## Schema |
|
|
| This dataset releases the **public** version — questions and options only, no answer keys (the held-out answer key lives in a private dataset, and submissions are scored against it by the leaderboard Space). |
|
|
| ```json |
| { |
| "example_id": 1, |
| "p_id": "A1_JAKE_DAY7_19_00_00_q001", |
| "identity": "A1_JAKE", |
| "query_time": "DAY7, 19:00:00", |
| "question": "What do I most often eat for breakfast?", |
| "options": { |
| "A": "Pancake", |
| "B": "Rice", |
| "C": "Burger", |
| "D": "Dumplings" |
| }, |
| "query_type": "Activity Pattern" |
| } |
| ``` |
|
|
| Note that **questions have 4-10 options** (letters A-J). The valid answer set for any given question is the keys of its `options` dict; Event Ordering questions tend to have the most options. |
|
|
| ## How to evaluate |
|
|
| 1. Get this dataset: |
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("Ted412/EgoMemReason")["test"] |
| ``` |
| 2. Get the underlying EgoLife video frames (separate license, see <https://egolife-ai.github.io/>) — we don't redistribute video here. |
| 3. For each item, sample frames from `(identity, query_time)` backwards in time and run your model to pick one letter from `options.keys()`. |
| 4. Format the predictions as a JSON list: |
| ```json |
| [ |
| {"example_id": 1, "predicted_answer": "A"}, |
| ... |
| ] |
| ``` |
| 5. Submit it on the leaderboard Space: <https://huggingface.co/spaces/Ted412/EgoMemReason>. Per-split + overall accuracy are computed automatically. |
|
|
| The reference inference scripts for 12 MLLMs and 5 agentic frameworks (Gemini, GPT-5, Qwen3-VL, InternVL3.5, Molmo2, VideoLLaMA3, InternVideo2.5, LongVA, AVP, Ego-R1, SiLVR, WorldMM, …) live in the [GitHub repo](https://github.com/Ziyang412/EgoMemReason). |
|
|
| ## License |
|
|
| - **EgoMemReason annotations** (this dataset): [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) — academic research and benchmarking are permitted; commercial use requires written permission. |
| - **EgoLife video frames** (not redistributed here): governed by the [EgoLife data license](https://egolife-ai.github.io/) — you must accept their terms separately. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{wang2026egomemreasonmemorydrivenreasoningbenchmark, |
| title={EgoMemReason: A Memory-Driven Reasoning Benchmark for Long-Horizon Egocentric Video Understanding}, |
| author={Ziyang Wang and Yue Zhang and Shoubin Yu and Ce Zhang and Zengqi Zhao and Jaehong Yoon and Hyunji Lee and Gedas Bertasius and Mohit Bansal}, |
| year={2026}, |
| eprint={2605.09874}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CV}, |
| url={https://arxiv.org/abs/2605.09874}, |
| } |
| ``` |
|
|
