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Lisa Lee
@rl_agent
Gemini pre-training & post-training
Joined February 2016
Posts
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    Five years ago, I left Google to pursue a PhD in Machine Learning. Tomorrow, I'm very excited to join Google Brain as a Research Scientist! Looking forward to meeting everyone :) My PhD thesis can be viewed at: leelisa.com/pdf/phd_thesis… Thesis defense: youtu.be/P4LH020ON3A
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    Update: I will be a Research Scientist at Google Brain starting this fall! Super grateful to all of the fantastic researchers I met through the interview process. Thanks for valuable career advice & research chats – I'll take these lessons with me in the next stage of my career!
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    Gemini is the most fun project I've worked on in my career. I feel so lucky to work with incredible teammates in Gemini. We all worked really hard for this public release. Looking forward to more learnings in 2024. Chat with Bard (running Gemini Pro): bard.google.com/chat
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    Just released our #ICML2018 paper "Gated Path Planning Networks" as well as a @PyTorch implementation for replicating our experiments: arxiv.org/abs/1806.06408 github.com/lileee/gated-p… - with Emilio Parisotto, @dchaplot, Eric Xing, @rsalakhu See you @icmlconf in Stockholm!
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    I wrote a Colab tutorial on MaxEnt RL: colab.research.google.com/drive/1VkoRfg_… It implements the graphical model from @svlevine's "RL as Inference" tutorial for a simple chain environment. Play around with the reward function to learn different policies using the forward-backward algorithm!
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    My dog Eevee 🐶 is featured in our recent research paper from Google @DeepMind: Barkour: Benchmarking animal-level agility with quadruped robots Inspired by dog agility competitions, we introduce a diverse and challenging obstacle course for robotic locomotion. (1/n)
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    I was a TA for @rsalakhu's 10-703 Deep Reinforcement Learning, with 500+ enrolled students. It was a little scary to hold office hours at first, but it got easier as I got to know more students. I was so touched to read these words from students. Thank you!
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    Excited to give two Contributed Talks @ #iclr2019 on Monday w/ Ben Eysenbach on our new work: Exploration & Meta-RL via State Marginal Matching leelisa.com/pdf/state_marg… w/ Ben, Emilio @rsalakhu @svlevine 12:15 @ TARL tarl2019.github.io/#schedule 15:50 @ SPiRL spirl.info/2019/program
    GIF
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    What makes it hard for robots to generalize to new environments? In our study, we broke down the notion of an “environment” into smaller, more manageable factors of variation, such as lighting or camera placement. sites.google.com/view/generaliz… 1/n
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    I'm excited to present our Gated Path Planning Networks paper at #ICML2018 today. Come say hi! Oral Talk: 14:10 @ A1 Poster: 18:15 - 21:00 @ Hall B #134 Paper: arxiv.org/abs/1806.06408 Code: github.com/lileee/gated-p… - with Emilio, @dchaplot, Eric, @rsalakhu
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    Our new work is featured in the @nytimes: RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control tl;dr We fine-tune a VLM to predict robot actions directly as text, and see emergent capabilities in the embodied agent. (1/n)
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    Visited @mcgillu in Montreal. Such a beautiful campus in a beautiful city 🇨🇦🍁
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    Video & slides for LIRE workshop @ #NeurIPS2019 are now up: sites.google.com/view/neurips20… Check out the Talks and Panel by @RaiaHadsell @tommmitchell Jeff Bilmes @pabbeel @YejinChoinka Tom Griffiths & more. Thanks to all speakers & presenters for making the workshop a success!
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    I just started at Stanford this week as a visiting researcher in @chelseabfinn's lab, and I'm also still part-time at Google Brain Robotics. If you're around in the area and would like to chat about research, please feel free to reach out anytime! (My office is in Gates)