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cs.RO2026

Zetta : An Efficient Closed-Loop Embodied Harness for Self-Evolving Physical Intelligence

Xin Ding, Liang Mi, Mingzhe Huang +12

Embodied agents are increasingly used to close the gap left by end-to-end policy models. Yet the agentic path has not realized closed-loop learning in physical execution: existing…

cs.RO2026

ActProbe: Action-Space Probe for Early Failure Detection of Generative Robot Policies

Bingjia Huang, Xiangyu Li, Xiang Wang +7

Generative robot policies fail unpredictably at deployment: they hesitate at critical moments, drift off-task, or commit to unrecoverable actions. Existing online failure detectors…

cs.CV2026

GRIP-VLM: Group-Relative Importance Pruning for Efficient Vision-Language Models

Mingzhe Huang, Weijun Wang, Xin Ding +7

In Vision-Language Models (VLMs), processing a massive number of visual tokens incurs prohibitive computational overhead. While recent training-aware pruning methods attempt to sel…

cs.AI2026

EmbodiSkill: Skill-Aware Reflection for Self-Evolving Embodied Agents

Ruofei Ju, Xinrui Wang, Xin Ding +12

Embodied agents can benefit from skills that guide object search, action execution, and state changes across diverse environments. Since embodied environments vary across layouts,…

cs.DC2026

Efficient Remote KV Cache Reuse with GPU-native Video Codec

Liang Mi, Weijun Wang, Jinghan Chen +3

Remote KV cache reuse fetches KV cache for identical contexts from remote storage, avoiding recomputation, accelerating LLM inference. While it excels in high-speed networks, its p…