1 citations · 1 across the 8 of their papers we have counts for
9 papers
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,…
Joint Agent Memory and Exploration Learning via Novelty Signals
Shizuo Tian, Xiaohong Weng, Rui Kong +9
In open-ended environments, exploration is fundamental for autonomous agents, yet current language model agents struggle with this. Effective exploration requires memory, but retai…
OxyGen: Unified KV Cache Management for VLA Inference under Multi-Task Parallelism
Xiangyu Li, Huaizhi Tang, Xin Ding +3
Embodied AI agents increasingly require parallel execution of multiple tasks, such as manipulation, conversation, and memory construction, from shared observations under distinct t…
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…