The rapid adoption of LLM applications is driving up serving cost, yet GPUs remain underutilized in practice due to single-model provisioning and highly variable, long-tailed workloads. Co-locating two or more LLMs on one GPU can improve utilization, but it requires fast and coordinated control of both KV cache/paramet...
Cun-Chi Lv, Xiao Shi, Zheng-Yu Lei et al.· IEEE International Conferenc...· 0 citations
Results show that endpoint correction improves the quality-latency trade-off of frozen flow-matching policies, and supports correction as an effective alternative to additional integration.
Zhi-Peng Tang, Xin-Da Chen, Wei-Ning Rao et al.· 0 citations
RoMAN-Flow (Robotic Manipulation with Autoregressive Normalizing Flows), an offline reinforcement learning framework that makes AR-NF policies practical for robotic manipulation by addressing this sampling bottleneck in both stages.
Shao-Xuan Wang, Guangting Zheng, Rui Huang et al.· 0 citations
The experimental results validate the effectiveness of the LabDex task design and demonstration data, and show that the benchmark supports the training and systematic evaluation of existing robotic policies across laboratory dexterous manipulation tasks at different levels, providing a foundation for further research a...
Zhipeng Tang, Sihan Chen, Sha Zhang et al.· 0 citations
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