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RoboPapers
311 posts
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RoboPapers
@RoboPapers
@chris_j_paxton, @micoolcho & @DJiafei geeking out weekly with authors of robotics AI papers. On YouTube / X / Spotify / Substack
youtube.com/@RoboPapers
Joined February 2025
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  • Pinned
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    RoboPapers
    @RoboPapers
    Jun 1
    3 of us @micoolcho @chris_j_paxton @DJiafei are super excited to help organize the Robotic Origami Competition at IROS (Sept 2026), along with @BitRobotNetwork @SharpaRobotics @LightwheelAI @hq_fang @sanatem @Noriaki_Hirose @gao_young Calling for teams!
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    RoboPapers
    @RoboPapers
    Oct 21, 2025
    Robots has a data problem, in that robotics data is rare. While human video is quite common, it’s not usually directly usable for robots for a variety of reasons, most significantly that it’s missing explicit, accurate robot actions. Instead, @jerthesquare_ proposes that we
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    RoboPapers
    @RoboPapers
    Nov 13, 2025
    With enough data, robots and AI can learn “world models” that let them predict the results of their actions. These models are a way to learn how embodied AI agents can perform a wide variety of useful tasks — but they require a huge amount of data. The team at General Intuition
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    RoboPapers
    @RoboPapers
    Mar 7, 2025
    RoboPapers Ep1 (with @DJiafei ) on sam2act.github.io Hosted by @chris_j_paxton @micoolcho
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    RoboPapers
    @RoboPapers
    Aug 13, 2025
    Robotics as a field faces a large data gap, and one of the most promising directions for solving it is sim-to-real robot learning. We talked with @Stone_Tao about ManiSkill3: a powerful, easy-to-use framework for generalizable sim-to-real learning. In particular, we learned
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    RoboPapers
    @RoboPapers
    Mar 20, 2025
    Full episode dropping tomorrow! Geeking out with @ToruO_O on toruowo.github.io/recipe/ (Sim-to-Real Reinforcement Learning for Vision-Based Dexterous Manipulation on Humanoids). Co-hosted by @chris_j_paxton & @micoolcho
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    RoboPapers
    @RoboPapers
    Mar 27, 2025
    Ep4 with @JasonMa2020 on generative-value-learning.github.io (Vision Language Models are In-Context Value Learners) Co-hosted by @chris_j_paxton & @micoolcho
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    RoboPapers
    @RoboPapers
    Jul 8, 2025
    Full episode dropping soon! Geeking out with @___Harald___ CTO at @comma_ai on Learning to Drive from a World Model blog.comma.ai/mlsim Co-hosted by @chris_j_paxton @micoolcho
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    RoboPapers
    @RoboPapers
    Oct 28, 2025
    Reasoning models have massively expanded what LLMs are capable of, but this hasn’t necessarily applied to robotics. Perhaps this is in part because robots need to reason over space, not just words and symbols; so the robotics version of a reasoning model would need to think in
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    RoboPapers
    @RoboPapers
    Mar 5, 2025
    Full episode dropping this Friday! 🤖 Geeking out on sam2act.github.io with @chris_j_paxton @micoolcho @DJiafei
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    RoboPapers
    @RoboPapers
    Oct 24, 2025
    Offline reinforcement learning is crucial for robotics, but does it scale? We talk to @seohong_park , who discusses how for long-horizon manipulation problems the answer may be no — at least not yet. But there are tricks that you can use to make it work effectively. Watch
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    RoboPapers
    @RoboPapers
    Aug 12, 2025
    Full episode dropping soon! Geeking out with @Stone_Tao on ManiSkill, an open framework for robotic simulation & training github.com/haosulab/ManiS… Co-hosted by @micoolcho @chris_j_paxton
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    RoboPapers
    @RoboPapers
    Sep 26, 2025
    Learning policies via imitation is extremely potent, but making sure those policies will generalize to out of distribution settings is still very hard. SAILOR proposes a solution in learning to search via a learned world model, which outperforms existing imitation approaches.
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    RoboPapers
    @RoboPapers
    May 26, 2025
    Ep#11 with @snasiriany @SteveTod1998 @abhirammaddukur @Lawrence_Y_Chen on Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulation co-training.github.io Co-hosted by @chris_j_paxton & @micoolcho
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