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Tianyu Li EasyPaperSniper
@SniperPaper
Founding Researcher@Dexmate | exRS@FAIR | GaTech PhD
easypapersniper.github.io
Joined September 2019
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  • user avatar
    Tianyu Li EasyPaperSniper
    @SniperPaper
    May 2
    Interesting works. Enhancing the capacity of low cost robots will make robots more accessible to everyone
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    Zhiyang (Frank) Dou
    @frankzydou
    May 1
    Excited to share that our work NeuralActuator: Neural Actuation Modeling for Robot Dynamics and External Force Perception has been accepted to #RSS2026! Your robot — even a low-cost one — can feel external forces without torque or tactile sensors. TL;DR: NeuralActuator is a
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    Tianyu Li EasyPaperSniper
    @SniperPaper
    Apr 25
    Our perception stack today is a mosaic — MoGe for depth/normals, SAM3 for segmentation, Grounding DINO for open-vocab detection — each with its own preprocessing and failure modes. Long-horizon tasks compound this: every subpolicy wants a different input. Collapsing all of it
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    Saining Xie
    AMI Labs
    @sainingxie
    Apr 23
    vision🍌 is here vision-banana.github.io if you got into computer vision the way I did, starting with pixel-level labeling tasks like segmentation, edges, depth, or surface normals, you’ll probably feel the same seeing these results -- something big has quietly shifted, and it’s
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    Tianyu Li EasyPaperSniper
    @SniperPaper
    Apr 25
    Coding agents are deployable today partly because we sandbox them: actions are validated and reversible before they touch production. Robots have no sandbox — the physical world has no undo. One core function of a world model is to be exactly that: a sandbox for the physical
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    Yann LeCun
    @ylecun
    Apr 24
    Replying to @ben_j_todd
    1. I never said LLMs were not useful. They are, particularly with all the bells and whistles that are being added to them. I use them. 2. A robot-rich future can't be built with AIs that don't understand the physical world and don't anticipate the consequences of their actions.
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    Tianyu Li EasyPaperSniper
    @SniperPaper
    Apr 9
    Here we announce the winners of our Build with Vega U Research Grant Program! Congratulations to the six proposals selected. @tomssilver @GuanyaShi @QianqianWang5 @_krishna_murthy @daniel_t_seita Yuxiong Wang
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    Dexmate
    @DexmateAI
    Apr 9
    We're thrilled to announce the recipients of the Dexmate Build with Vega U Research Grant Program. Out of an incredible pool of proposals, six research teams have been selected to receive a Vega U dual-arm manipulation platform to advance their work in dexterous manipulation,
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    Tianyu Li EasyPaperSniper
    @SniperPaper
    Mar 21
    We're officially launching the Dexmate Research Grant Program. Apply here: lnkd.in/g2rTqCvd
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    Dexmate
    @DexmateAI
    Mar 21
    💌 A message from our CEO, Tao Chen. In this video, he shares why we’re launching the Dexmate's Build with Vega U Research Grant Program and the future we’re building toward. Our mission is simple: make intelligent robotics accessible to the people pushing research forward. 💡
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