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20162026
most citedDeep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability

180 citations · 578 across the 40 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

cs.RO2026

FCTS: Failure-Guided Curriculum Tree Search Over Generated Terrain for Legged Parkour

Narayanan Palghat Parameswaran, Dong-Ki Kim, Jay Patrikar +4

Quadruped parkour policies handle canonical obstacles well, but their training curricula often miss the irregular, compound geometry of industrial and disaster-response sites, wher…

cs.RO2026

PriMoRetarget: Humanoid Motion Transfer Through Prioritized Motion Retargeting

Nicholas Ioannidis, Dun Yang, Max Smith +5

Motion retargeting is a critical preprocessing step for transferring human motion data to humanoid robots. While existing methods are effective for single-character motions, intera…

cs.CV2026

PhyMotion: Structured 3D Motion Reward for Physics-Grounded Human Video Generation

Yidong Huang, Zun Wang, Han Lin +6

Generating realistic human motion is a central yet unsolved challenge in video generation. While reinforcement learning (RL)-based post-training has driven recent gains in general…

cs.RO2026

Simulation Distillation: Pretraining World Models in Simulation for Rapid Real-World Adaptation

Jacob Levy, Tyler Westenbroek, Kevin Huang +6

Robot learning requires adaptation methods that improve reliably from limited, mixed-quality interaction data. This is especially challenging in long-horizon, contact-rich tasks, w…

cs.RO2026

World Model Failure Classification and Anomaly Detection for Autonomous Inspection

Michelle Ho, Muhammad Fadhil Ginting, Isaac R. Ward +4

Autonomous inspection robots for monitoring industrial sites can reduce costs and risks associated with human-led inspection. However, accurate readings can be challenging due to o…