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20172026
most citedSelf-Monitoring Navigation Agent via Auxiliary Progress Estimation

134 citations · 440 across the 79 of their papers we have counts for

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19 papers · 1 filter

cs.RO2026

SafeManip: A Property-Driven Benchmark for Temporal Safety Evaluation in Robotic Manipulation

Chengyue Huang, Khang Vo Huynh, Sebastian Elbaum +2

Robotic manipulation is typically evaluated by task success, but successful completion does not guarantee safe execution. Many safety failures are temporal: a robot may touch a cle…

cs.RO2026

Video2Sim2Real: Full-Stack Autonomous Dexterous Skill Acquisition from a Single Human Video

Yunhai Han, Jianuo Qiu, Linhao Bai +14

Human manipulation videos are a convenient and intuitive source for robot learning. However, directly transferring human dexterity to robots remains challenging due to perception e…

cs.RO2026

SeeTraceAct: Visibility-Aware Latent Planning from Cross-Embodiment Demonstration Videos

Jaehyeon Son, Junhyun Kim, Kyle Kam +7

Vision-language-action models (VLAs) are promising general-purpose robot policies, but adapting them to new tasks typically requires costly task-specific teleoperation data. As an…

cs.RO2026

Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring

Seongheon Park, Wendi Li, Changdae Oh +4

Vision-Language-Action (VLA) models enable robots to follow natural language instructions and generalize across diverse tasks, but they remain vulnerable to execution failures that…

cs.RO2025

EVE: A Generator-Verifier System for Generative Policies

Yusuf Ali, Gryphon Patlin, Karthik Kothuri +4

Visuomotor policies based on generative such as diffusion and flow-matching have shown strong performance for robotics applications but degrade under distribution shifts, demonstra…

cs.RO2025

Hierarchical Reinforcement Learning and Value Optimization for Challenging Quadruped Locomotion

Jeremiah Coholich, Muhammad Ali Murtaza, Seth Hutchinson +1

We propose a novel hierarchical reinforcement learning framework for quadruped locomotion over challenging terrain. Our approach incorporates a two-layer hierarchy in which a high-…