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README.md

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-- **[2025-3]** 👓👓 Introducing **`EgoLife`**: Towards Egocentric Life Assistant. For one week, six individuals lived together, capturing every moment through AI-powered wearable glasses, creating the EgoLife dataset. Based on this we build models and benchmarks to drive the future of AI life assistants that capable of recalling past events, tracking habits, and providing personalized, long-context assistance to enhance daily life.
+- **[2025-3]** 👓👓 Introducing **`EgoLife`**: Towards Egocentric Life Assistant. For one week, six individuals lived together, capturing every moment through AI-powered wearable glasses, and creating the EgoLife dataset. Based on this we build models and benchmarks to drive the future of AI life assistants that capable of recalling past events, tracking habits, and providing personalized, long-context assistance to enhance daily life.
 
-    [Homepage](https://egolife-ai.github.io) | [Github](https://github.com/EvolvingLMMs-Lab/EgoLife) | [Paper](https://huggingface.co/papers/2503.03803)
+    [Homepage](https://egolife-ai.github.io) | [Github](https://github.com/EvolvingLMMs-Lab/EgoLife) | [Blog](https://egolife-ai.github.io/blog) | [Paper](https://huggingface.co/papers/2503.03803) | [Demo](https://egolife.lmms-lab.com/)
 
 - **[2025-1]** 🎬🎬 Introducing **`VideoMMMU`**: Evaluating Knowledge Acquisition from Professional Videos. Spanning 6 professional disciplines (Art, Business, Science, Medicine, Humanities, Engineering) and 30 diverse subjects, Video-MMMU challenges models to learn and apply college-level knowledge from videos.