7 papers · 1 filter
Replicate What Varies: Resource Sharing for Domain-Randomized Embodied Simulation
Zixu Hao, Weijun Wang, Xiangyu Li +4
Simulation provides a low-cost sandbox where embodied agents can attempt tasks, observe outcomes, and learn from experience. Running many diverse simulation environments concurrent…
EBRL: Asynchronous Embodied RL by Multi-Grained Resource Management
Liang Mi, Weijun Wang, Bowen Gao +12
Embodied reinforcement learning (RL) improves model capabilities with a pipeline of environment simulation, action generation, and model updates. These stages show heterogeneous CP…
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…
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…
MemCompiler: Compile, Don't Inject -- State-Conditioned Memory for Embodied Agents
Xin Ding, Xinrui Wang, Yifan Yang +9
Existing memory systems for embodied agents typically inject retrieved memory as static context at episode start, a paradigm we term Ahead-of-time Monolithic Memory Injection (AMMI…
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…
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…