Yuchen Cui @YuchenCui1
Postdoc @Stanford in Interactive Robot Learning 🤖🤖🤖 | previously CS PhD @UTAustin, BS @PurdueECE | I am on the academic job market the 2023-2024 season! web.stanford.edu/~yuchenc/ Stanford, CA Joined August 2011-
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Reward functions are often hard or impossible to design. If you're working on RL without a predefined reward function (RLHF, unsupervised, exploration etc.), consider submitting to the RLBrew workshop! Deadline May 3rd.
Reward functions are often hard or impossible to design. If you're working on RL without a predefined reward function (RLHF, unsupervised, exploration etc.), consider submitting to the RLBrew workshop! Deadline May 3rd.
Announcing the Reinforcement Learning Beyond Rewards workshop at the first @RL_Conference. Think that rewards aren't enough for RL? Working on RLHF? Thinking of alternative ways of alignment? Creating a foundational model for RL? or have ideas on task-agnostic RL algo? Join us
We are presenting this work at #NeurIPS2023 Wednesday morning at poster #423. Come and check it out if you are also in New Orleans! ⚜️
We are presenting this work at #NeurIPS2023 Wednesday morning at poster #423. Come and check it out if you are also in New Orleans! ⚜️
How can robots 🤖 𝘳𝘦𝘮𝘦𝘮𝘣𝘦𝘳 human language feedback 🗣️ over time? We introduce DROC: a method for distilling and retrieving generalizable knowledge from online language corrections. Paper: arxiv.org/abs/2311.10678 Website: sites.google.com/stanford.edu/d…
Thrilled to announce the first annual Reinforcement Learning Conference @RL_Conference, which will be held at UMass Amherst August 9-12! RLC is the first strongly peer-reviewed RL venue with proceedings, and our call for papers is now available: rl-conference.cc. 🧵
Really excited for what RT-X can enable in robot learning moving forward! Amazing collaboration with a wonderful group of people in academia and industry!
Really excited for what RT-X can enable in robot learning moving forward! Amazing collaboration with a wonderful group of people in academia and industry!
Choosing the right action space is critical in imitation learning. Our method HYDRA can dynamically switch between different action abstractions, which reduces state distribution shift at test time. (1/6) Paper: arxiv.org/abs/2306.17237 Website: tinyurl.com/3mc6793z
In imitation learning (IL), we often focus on better algorithms, but what about improving the data? What does it mean for a dataset to be high quality? Our work takes a first step towards formalizing and analyzing data quality. (1/5) arxiv.org/abs/2306.02437
Thanks Scott for all the support and guidance throughout my PhD!
How does the design of ML interaction influences the human in the loop and the learning outcomes? Check out our latest survey paper on this!
How does the design of ML interaction influences the human in the loop and the learning outcomes? Check out our latest survey paper on this!
Congrats Scott!
Excited to share our work EMPATHIC on learning from implicit human feedback! To be presented at #CoRL2020 tomorrow at 11:10AM PT. website: sites.google.com/utexas.edu/emp… video: youtube.com/watch?v=sTvNUp… w/ @Qipingzhang2015 @ale_allievi Peter Stone @scottniekum @BradKnox
Correction: youtube live link youtu.be/PZeFYjcbnMA Going live in 23 min!
Correction: youtube live link youtu.be/PZeFYjcbnMA Going live in 23 min!
Ken Goldberg @Ken_Goldberg
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28 Followers 5K FollowingRoboDepot🤖 @RoboDepot
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229K Followers 3K Following @NVIDIA Sr. Research Manager & Lead of Embodied AI (GEAR Lab). Creating foundation models for Humanoid Robots & Gaming. @Stanford Ph.D. @OpenAI's first intern.Danfei Xu @danfei_xu
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13K Followers 2K Following Anti-cynic. Artificial narrow intelligence. Autonomous vehicles, multi-agent learning, and transportation. RS at Apple, Asst. Prof at @nyutandon. He/him.Yifeng Zhu 朱毅枫 @yifengzhu_ut
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941 Followers 151 Following Associate Professor @USC. PhD from @CMU_Robotics, MS from @MIT, MEng from #UTokyo, BS from @NTUA. Previously worked at @SquareEnix in Tokyo.Soroush Nasiriany @snasiriany
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391 Followers 43 Following The RSS Pioneers 2024 Workshop will be held at #RSS2024 (@RoboticsSciSys) in Delft, the Netherlands! Managed by the #RSSPioneers2024 publicity chairs.Vaibhav Unhelkar @VaibhavUnhelkar
105 Followers 32 Following Assistant Professor of Computer Science, Rice University #robotics #AI #HRIBrett Adcock @adcock_brett
171K Followers 14 Following Founder @Figure_robot (AI Robotics) & Archer Aviation (NYSE: ACHR)Tian Gao @TianGao_19
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4.4M Followers 361 Following Get #XiaomiFanFestival2024 exclusive discounts. Visit: https://t.co/v5gD57oMcOJonathan Haidt @JonHaidt
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282 Followers 15 FollowingKarthik Mahadevan @karthikm0
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1K Followers 224 Following Postdoc at @berkeley_ai. PhD @UniFreiburg. Prev. intern @NVIDIAAI. Research on robotics, language, computer vision, MLFrom the LLaMa 3 blogpost - they use a combination of rejection sampling, DPO and PPO for post-training. Really interested to know what tasks/parts of the process each algorithms benefits the most.
We have a new preprint out - your language model is not a reward, it’s a Q function! 1. The likelihood of the preferred answer must go down - it’s a policy divergence 2. MCTS guided decoding on language is equivalent to likelihood search on DPO 3. DPO learns credit assignment
Reward functions are often hard or impossible to design. If you're working on RL without a predefined reward function (RLHF, unsupervised, exploration etc.), consider submitting to the RLBrew workshop! Deadline May 3rd.
Announcing the Reinforcement Learning Beyond Rewards workshop at the first @RL_Conference. Think that rewards aren't enough for RL? Working on RLHF? Thinking of alternative ways of alignment? Creating a foundational model for RL? or have ideas on task-agnostic RL algo? Join us
Looking fwd to presenting a new talk: "Data is All You Need: Large Robot Action Models and Good Old Fashioned Engineering" @Stanford Robotics Seminar on Friday: stanfordasl.github.io/robotics_semin…
Congratulations to Dr. Erin Botti from @core_robotics on her successful PhD defense yesterday on "Improving Learning from Demonstration in Real-World Scenarios!" Check out her award-winning papers here: ieeexplore.ieee.org/document/98896… drive.google.com/file/d/1H2ZkY_…
We start this week's #RSSPioneers throwbacks by celebrating Yifeng Zhu (@yifengzhu_ut), a fifth-year Ph.D. student at @UTAustin. His research focuses on data-efficient learning of robot manipulation skills...but also features coffee! How so? Read on below! ☕️🧵
I had a great experience attending the Pioneers Workshop! Please stay tuned for the next cohort of pioneers!
We start this week's #RSSPioneers throwbacks by celebrating Yifeng Zhu (@yifengzhu_ut), a fifth-year Ph.D. student at @UTAustin. His research focuses on data-efficient learning of robot manipulation skills...but also features coffee! How so? Read on below! ☕️🧵
Excited to announce 🥁 the second speaker, Biwei Huang @huang_biwei's talk will discuss "Enhancing Reinforcement Learning through Causal Representations and Graph Structures"
Wouldn't it be cool to just talk to your robot 🤖 or smart glass agent 🕶️ in natural language? ✅ Hey 🕶️ do you remember where I left my badge? ✅ Hey 🤖 I'm hungry and driving back from work, do I have any fruits left? We're (@AIatMeta) working on this Embodied Question…
We at @GRASPlab hosted @ericjang11 last week for a thought-provoking talk on Humanoid robots and 1X! The full recording is up now, check it out!
Nice talk on the technical approach to intelligent humanoids at 1X! grasp.upenn.edu/events/spring-… As usual for @ericjang11’s spicy takes, I agree strongly with 60%, ambivalent on 20%, and disagree with 20%. Highly recommend a watch! 💯
We are excited to announce the release of our Agent API in public beta along with our Agent Playground @MultiOn_AI 🚀🚀 Our Agent API is the first-ever autonomous API that allows going from natural language to web actions using our Language Action Models (LAMs) all running in…
Introducing Agent API: bringing actions to your devices and applications multion.ai/blog/agent-api…
Announcing the Reinforcement Learning Beyond Rewards workshop at the first @RL_Conference. Think that rewards aren't enough for RL? Working on RLHF? Thinking of alternative ways of alignment? Creating a foundational model for RL? or have ideas on task-agnostic RL algo? Join us
The DROID dataset is out now! Increasing scene and motion diversity of real robot datasets to the extreme by collecting robot manipulation data in the wild.
After two years, it is my pleasure to introduce “DROID: A Large-Scale In-the-Wild Robot Manipulation Dataset” DROID is the most diverse robotic interaction dataset ever released, including 385 hours of data collected across 564 diverse scenes in real-world households and offices
The Path to Autonomy is paved with Simulation! The focus on building the best data engines for Embodied AI & Robotics has been a core mission at @NVIDIARobotics I am so excited to share that the simulation effort we have been working on for the last 2+ years will be part of…
After two years, it is my pleasure to introduce “DROID: A Large-Scale In-the-Wild Robot Manipulation Dataset” DROID is the most diverse robotic interaction dataset ever released, including 385 hours of data collected across 564 diverse scenes in real-world households and offices
We’ve been working on DROID for a long time… excited to see it’s finally released! Huge congrats to everyone, especially @SashaKhazatsky and @KarlPertsch.
After two years, it is my pleasure to introduce “DROID: A Large-Scale In-the-Wild Robot Manipulation Dataset” DROID is the most diverse robotic interaction dataset ever released, including 385 hours of data collected across 564 diverse scenes in real-world households and offices
@schuld_eth A groundhog named chunk has been stealing a farmer's crop from Delaware for 4 years & eats it in front of a camera
Robots need to be transparent about their understanding of the world, capabilities, & intents. GenEM generates expressive robot motion by directly using the code-writing capabilities of large language models. Excited that GenEM is recognized as best technical paper at #HRI2024
(1/9) Robots today are not expressive but have to perform tasks in environments where communicating with humans is critical. We appropriate LLMs which have shown the capability to create task plans and write policy code, to make robots more expressive.
I really hope humanoid startups can say something about the success rate when they post new demos…
With OpenAI, Figure 01 can now have full conversations with people -OpenAI models provide high-level visual and language intelligence -Figure neural networks deliver fast, low-level, dexterous robot actions Everything in this video is a neural network:
This is going to be the year of hands and dexterous manipulation :) A sneak-peak into what's been cooking in our lab: