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InstanceBench: Diagnosing Referential Reasoning and Target Identity in Referring Expression Segmentation
Yuchen Li, Shaoyang Zhou, Yiran Wang +5
Referring Expression Segmentation (RES) links natural-language descriptions to pixel-level object masks. Yet standard evaluation provides limited insight into instance-level refere…
Reconstruct, Practice, Go Real: Guided Self-Improvement for Embodied Agents
Yen-Jen Wang, Haozhe Jiang, Shuying Deng +7
Building reliable robot capabilities across diverse tasks requires substantial human effort to develop and maintain skills, design rewards, and integrate perception with control. W…
SimEX: Simulation-Integrated Robotics AutoResearch
Jiaheng Hu, Roberto Martin-Martin, Peter Stone +3
Coding agents powered by large language models (LLMs) have shown remarkable abilities to autonomously reason about and achieve goals in the digital world. However, bringing this su…
Counterfactual Video Generation Enables Scalable Humanoid Loco-Manipulation
Zihan Wang, Zhen Wu, Pieter Abbeel +6
Teaching humanoids loco-manipulation skills, such as carrying diverse objects, via visual imitation is a promising path toward generalist robots. However, collecting diverse, high-…
VLK: Learning Humanoid Loco-Manipulation from Synthetic Interactions in Reconstructed Scenes
Yen-Jen Wang, Jiaman Li, Sirui Chen +9
Perception-based humanoid loco-manipulation requires connecting egocentric observations and task instructions to whole-body motion. Learning this mapping requires synchronized egoc…
Scalable Behavior Cloning with Open Data, Training, and Evaluation
Arthur Allshire, Himanshu Gaurav Singh, Ritvik Singh +15
We introduce ABC, a fully open-source stack for manipulation with behavior cloning. At its core is ABC-130K: the largest open-source teleoperation dataset to date, featuring 3,500…
LadderMan: Learning Humanoid Perceptive Ladder Climbing
Siheng Zhao, Yuanhang Zhang, Ziqi Lu +6
Humanoid robots hold great promise for operating in human-centered environments, yet ladder climbing remains one of the most challenging tasks due to sparse footholds and handholds…
Cross-Hand Latent Representation for Vision-Language-Action Models
Guangqi Jiang, Yutong Liang, Jianglong Ye +6
Dexterous manipulation is essential for real-world robot autonomy, mirroring the central role of human hand coordination in daily activity. Humans rely on rich multimodal perceptio…
Flow Policy Gradients for Robot Control
Brent Yi, Hongsuk Choi, Himanshu Gaurav Singh +9
Likelihood-based policy gradient methods are the dominant approach for training robot control policies from rewards. These methods rely on differentiable action likelihoods, which…
Perceptive Humanoid Parkour: Chaining Dynamic Human Skills via Motion Matching
Zhen Wu, Xiaoyu Huang, Lujie Yang +8
While recent advances in humanoid locomotion have achieved stable walking on varied terrains, capturing the agility and adaptivity of highly dynamic human motions remains an open c…
RPL: Learning Robust Humanoid Perceptive Locomotion on Challenging Terrains
Yuanhang Zhang, Younggyo Seo, Juyue Chen +7
Humanoid perceptive locomotion has made significant progress and shows great promise, yet achieving robust multi-directional locomotion on complex terrains remains underexplored. T…