ToyBlocks is a controlled world for robot learning
Hugging Face published an Allen Institute for AI post; the available item gives only the project title.
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16 stories, newest first · one card per story
Stories tagged #robot-learning
A2-MEAS embodied framework reports BEHAVIOR and real-robot scores
Authors report 0.6411 Q-score on 100 public tasks and 57.92% success on 12 real-robot tasks versus 26.67% for pi0.5.
Open-HumanScale Scales Human Video for Robot Learning
Open-HumanScale-50K corpus and HumanWAM models pretrained on 50k hours of egocentric video achieve high success rates on robot benchmarks.
Pixel co-designed robot system learns general-purpose mobile manipulation
Pixel integrates hardware, teleoperation, whole-body control, and policy learning for dexterous mobile tasks.
ODE Policy learns robot action dynamics rather than discrete actions
After one epoch it reports 5.9 times flow matching's success and the highest rate on 14 real-world robot tasks.
WorldBridge Boosts Task Generalization in World Action Models
WorldBridge separates video and action experts to achieve state-of-the-art results on RoboTwin 2.0 and other benchmarks.
SO-101 Bench benchmarks language-conditioned spatial robot manipulation
A simulated twin matched the real arm's policy ranking exactly, though simulation overestimated success.
Paper maps recursive self-improvement pathways for physical robots
Reviewed physical studies show behavioral and procedure gains, but none isolate improvement that comes from recursion itself.
Hierarchical Residual Policy Learning for Real-World Mobile Manipulation with Sparse Human Guidance
HiRe-MoMa fine-tunes real-world mobile manipulation policies in about 30 minutes using sparse human guidance.
Modeling and Understanding Neural Weights of Humanoid Policies with Diffusion
Researchers generate deployable Unitree G1 humanoid controllers by diffusing learned policy weights.
Rephrase Before You Act: Characterizing and Mitigating Language Sensitivity in Vision-Language-Action Models
One-word instruction edits swing VLA success sharply; rule-based rephrasing improves frozen policies without retraining.
RLHND: Video Foundation Models as Physically Grounded Hand Trackers for Robot Learning
RLHND turns the Cosmos 3 video model into a tracker estimating hand pose, contact, and force for robot learning.
RoboCoach: World Models as Active Coaches for Compositional Robot Skills
RoboCoach uses a world model to target robot skill demos, lifting Franka success from 13.3% to 75%.
RLE-Bench: A Qualifying Exam for Coding Agents as Robot Learning Engineers
RLE-Bench scores coding agents as robot learning engineers across four robotics workflows.
InternW0-Δ: A World Action Model Bridging Predictive Dynamics and Actions with 20K+ Hours of Open Data
InternW0-Δ is a world action model pretrained on over 20,000 hours of open robot and human data.
Embedding Physics Priors in Robot Learning: A Survey
A survey reviews physics-embedded robot learning, proposing a unified taxonomy and arguing for its benefits over purely data-driven methods.