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updated my portfolio! you can now fight the little guide robot when it steals website pieces goldpig888.github.io
Thanks for the feedback! To clarify, it’s 5 trials/task across 10 tasks. We’ll update to 15 trials/task. With 7 policies already evaluated, that’s ~6–8 hours per policy. That's challenge of real-world evaluation, but we’re committed! @JiahuiZhang__32 @alexhuang1029 @maylynn_e
5 trials on this leaderboard is a highlight reel. I'd want intervals, cycle time, jam recovery, overrides and intervention data. irvlutd.github.io/VLAReplica/#le…
@bidhan That's exactly why RobotReplica exists. One standardized evaluation so results aren't tied to whatever robot happens to be under each model. Check it out! :) robot-replica.org
We finished evaluating MolmoAct2 on VLA-Replica! It shows better OOD performance than π0.5. Check out the details from @maylynn_e @alexhuang1029 @JiahuiZhang__32 below 👇 We’ll keep benchmarking frontier models for robot manipulation in the real world. Next up: GPT-6 Astra!
Finished fine-tuning MolmoAct2 on our VLA-Replica SO-101 setup, using 50 demonstrations per task! One result I find interesting: it outperforms π₀.₅ on OOD by 10%. Check out our leaderboard: irvlutd.github.io/VLAReplica/#le… pic.x.com/27qkS6Swfh
Really cool to see evaluation done in such a systematic and reproducible way. Standardized evaluation is one of the hardest problems out there right now!
We finished evaluating MolmoAct2 on VLA-Replica! It shows better OOD performance than π0.5. Check out the details from @maylynn_e @alexhuang1029 @JiahuiZhang__32 below 👇 We’ll keep benchmarking frontier models for robot manipulation in the real world. Next up: GPT-6 Astra!
@VilleKuosmanen @YuXiang_IRVL @alexhuang1029 @JiahuiZhang__32 All the MolmoAct2 training/fine-tuning settings are in the "Training & Model Parameters" table right under here: robot-replica.org/vla-replica#le… Good luck on your evals :)
ID: MolmoAct2 reaches 46% success, compared to 54% for π₀.₅, ~30% for SmolVLA, and ~30% for π₀ irvlutd.github.io/VLAReplica/sce… OOD: MolmoAct2 reaches 45% success across 8 VLA-Replica-OOD tasks, compared with 35% for π₀.₅, 30% for SmolVLA, and 30% for π₀ irvlutd.github.io/VLAReplica/sce…
Finished fine-tuning MolmoAct2 on our VLA-Replica SO-101 setup, using 50 demonstrations per task! One result I find interesting: it outperforms π₀.₅ on OOD by 10%. Check out our leaderboard: irvlutd.github.io/VLAReplica/#le… pic.x.com/27qkS6Swfh
We finally got a chance to test MolmoAct 2 on our VLA-Replica setup! @DJiafei @hq_fang Here’s one successful “zero-shot” case from our side :) @maylynn_e @alexhuang1029 @JiahuiZhang__32 We put “zero-shot” in quotes since we don’t know what data this MolmoAct 2 model was trained on. Two preliminary observations from our tests: • It seems quite sensitive to object color. Detailed instructions with color can help. • It struggles with precise grasping of small objects, such as a block.
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4K Followers 1K Following gentleman scientist 🤖 @armnet_dev building the world's largest open arm farm 🇫🇮🇬🇧
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216 Followers 936 Following PhD @IRVLUTD | Prev: RA @USC CLVR lab, Lira Lab | Intern @fieldai_, Horizon Robotics | Master @USC
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38 Followers 22 Following Honors EE @UT_Dallas | Researcher @IRVLUTD | 2025 ISEF Finalist
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