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SpaceCache: Intermediate Feature Reuse for Efficient Semantic Segmentation on Point Cloud Streams
Dongheon Yang, Beomseok Kang, Jae-Joon Kim
Point-cloud streams are central to autonomous driving and robotics, yet existing segmentation networks process every frame from scratch, although consecutive frames largely overlap…
Accelerating VLA Inference with Perturbation Informed Execution
Jehun Lee, Hajun Lee, Jimin Ryu +4
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 predic…
Joint Subspace Sparse Attention for Efficient Long-Context Decoding
Jiwon Song, Yoongon Kim, Jae-Joon Kim
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 fi…
KVCMAS: Efficient KV cache Correction for Shared Context in Multi-Agent Systems
Hyesung Jeon, Hyeongju Ha, Seoyoung Lee +2
Prompt-specialized multi-agent systems enable multiple agents to share a model while performing complementary roles to solve complex tasks. However, agent-specific prefixes change…
Token Sparse Attention: Efficient Long-Context Inference with Interleaved Token Selection
Dongwon Jo, Beomseok Kang, Jiwon Song +1
The quadratic complexity of attention remains the central bottleneck in long-context inference for large language models. Prior acceleration methods either sparsify the attention m…