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X Square Robot
@XSquareRobot
Building generalist robots for real-world deployment Open models, benchmarks & uncut demos. WALL-OSS-0.5 ยท WALL-WM ยท XRZero-G0 โ†“
๊ฐ€์ž… April 2025
174 ํŒ”๋กœ์ž‰ ์ค‘    1.9K ํŒฌ
Excited to join Saturday Robotics ร— IROS 2026 in Pittsburgh! ๐Ÿค– We will present X2Real, our extensive simulation benchmark for evaluating real-world generalist robot policiesโ€”featuring 44 hierarchical, long-horizon tasks across 10 capability dimensions. We look forward to sharing our latest work and connecting with researchers and builders advancing robot learning, simulation-to-real transfer, and embodied AI. ๐Ÿ“ Pittsburgh ๐Ÿ“… September 28, 2026 ๐Ÿ‘‰๐Ÿป See you there!
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๐Ÿพ๐Ÿฒ Saturday Robotics x IROS 2026 โ€” Robotics Research Night ๐Ÿ‘‰๐Ÿป Weโ€™re bringing a high-signal evening of robotics research to Pittsburgh on September 28. After a full day at IROS, weโ€™ll bring together researchers, engineers, founders, students, and investors for technical discussions, networking, and a series of ~10-minute lightning talks. Tentative preview of the current lineup: ๐Ÿค– 1. PAC-MAN: Perception-Aware CBF-RL for Whole-Body Safety in Humanoid Dodgeball Gary Yang @lzyang2000 (@Caltech) Perception-aware reinforcement learning + Control Barrier Functions for whole-body humanoid safety. Demonstrated on a Unitree G1, with 19/20 successful dodges and zero falls in real-world experiments. ๐Ÿง  2. How In-Context Learning Is Reshaping Robot Learning Data at Scale AaronLi (@RhodaAI) Exploring how in-context learning can change the way we think about robot learning data, scaling, and generalization. ๐Ÿงช 3. X2Real: An eXtensive Simulation Benchmark for Real-World Generalist Policies Liangwang Ruan (@XSquareRobot) A new simulation benchmark built around faithfulness, diversity, and fairness, with 44 hierarchical long-horizon tasks across 10 capability dimensions and a reported 0.84 simulation-to-real correlation. ๐Ÿฆพ 4. Rethinking Generalist Robotic Manipulation: Architecture, Data and Inference for Real-World Deployment Peiyan Li (Chinese Academy of Sciences, @CAS__Science) 3D VLA architectures, memory augmentation, ego/UMI human priors, large-scale robot pretraining, and inference-time contextual learning for deployable generalist manipulation. ๐ŸŽฏ 5. HiRE: Hindsight Reward Editing for Policy Finetuning Haoyi Niu @t641769919 (@UCBerkeley) Accepted at CoRL 2026. A training-free approach to reward editing that uses successful and failed trajectories to identify โ€œtrap statesโ€ and provide denser, control-aware feedback for RL. ๐Ÿ”ฅ 6. Lightning Talk โ€” Open Slot Weโ€™re opening one additional slot for a technically deep research talk, new project, frontier paper, demo, open problem, or startup technical insight. 10 minutes. A few slides. One sharp technical idea. No fluff. Topics include World Models, Physical AI, Humanoids, VLAs, Robot Foundation Models, Manipulation, RL, Simulation & Sim-to-Real, Spatial Intelligence, Computer Vision, and Embodied AI. ๐Ÿ“ Pittsburgh ๐Ÿ“… September 28, 2026 ๐Ÿ•  5:30โ€“9:30 PM ๐Ÿพ Networking + Technical Talks + Research Discussion ๐Ÿ“ฉ junfanzhu98@gmail.com See you in Pittsburgh. ๐Ÿค– #IROS2026# #Robotics# #PhysicalAI# #RobotLearning# #WorldModels# #HumanoidRobotics# #VLA# #EmbodiedAI# #RobotFoundationModels#
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