Yanlai Yang
@YanlaiYang
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PhD student @nyuniversity @agentic_ai_lab
New York, NY
Joined August 2021
Excited to present my work at CoLLAs 2025 @CoLLAs_Conf! In our paper https://t.co/mm8cmxtvhO, we tackle the challenge of self-supervised learning from scratch with continuous, unlabeled egocentric video streams, where we propose to use temporal segmentation and a two-tier memory.
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Just finished my first in-person NeurIPS journey. It’s great to meet many friends, old ones and new ones. Happy to see that my work is well-received in the poster session!
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I’ll be presenting the poster of this work at #NeurIPS2024 tomorrow from 11-2, at West 5609. Welcome everyone to check it out and happy to chat!
🔍 New LLM Research 🔍 Conventional wisdom says that deep neural networks suffer from catastrophic forgetting as we train them on a sequence of data points with distribution shifts. But conventions are meant to be challenged! In our recent paper led by @YanlaiYang, we discovered
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A gloomy day in New York couldn't dampen the fun with new friends and new research at NYC CV Day 🥳 Excited to share our updated LifelongMemory framework that leverages LLMs for long-form video understanding, which achieves SOTA on EgoSchema! https://t.co/D75IWYlK4R
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🔍 New LLM Research 🔍 Conventional wisdom says that deep neural networks suffer from catastrophic forgetting as we train them on a sequence of data points with distribution shifts. But conventions are meant to be challenged! In our recent paper led by @YanlaiYang, we discovered
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How should we pretrain for robotic RL? Turns out the same offline RL methods that learn the skills serve as excellent pretraining. Our latest experiments show that offline RL learns better representations w/ real robots: https://t.co/vUFWTcl5xH
https://t.co/9Q9oUdXefT Thread>
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Reusable datasets, such as ImageNet, are a driving force in ML. But how can we reuse data in robotics? In his new blog post, Frederik Ebert talks about "bridge data": multi-domain and multi-task datasets that boost generalization of new tasks: https://t.co/JbIbC9X1I1 A thread:
bair.berkeley.edu
The BAIR Blog
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