Action-chunking vision-language-action (VLA) models predict sequences of future robot actions. Under fixed-horizon execution, the robot executes a fixedlength prefix of each predicted chunk before invoking the policy again, leaving the remaining predictions unused. For a given number of executed actions, short executio...
Jehun Lee, Ha-Jun Lee, Jimin Ryu et al.· 0 citations
Sparse attention reduces the KV-cache traffic that dominates long-context LLM decoding, but practical methods largely operate at coarse granularity. Token-level selection offers finer control, yet presents two challenges: low-dimensional scoring may lose query--key structure needed for accurate ranking, while gathering...
KVCMAS is presented, an online KV cache correction framework that represents cross-agent cache deviations using compact low-rank states and seamlessly chains corrections along the agent workflow without an additional reference prefill, establishing KVCMAS as an accurate and scalable KV cache sharing approach for prompt...
Hyesung Jeon, Hyeongju Ha, Seoyoun Lee et al.· 0 citations
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