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cs.AI2026

RelaxKV: Recomputation Guided by the Query with Sparse Context Attention for Efficient KV Cache Reuse

Ruoling Qi, Yirui Liu, Xuaner Wu +5

Cross-request KV caching reduces the prefill cost of Retrieval-Augmented Generation (RAG), but conventional prefix caching severely limits cache reuse across requests. Position-Ind…

cs.AI2026

Just Let Linear States Forget the Distant Past: Prefix Caching via Suffix Replay for Hybrid LLMs

Yirui Liu, Ruoling Qi, Xuaner Wu +6

Hybrid LLMs interleave full-attention layers with linear-attention layers to reduce long-context inference cost, but this structure complicates prefix caching. Full-attention KV ca…

cs.AI2026

REVISE: Validity-Guided Recovery for Online Revisions in Agent Workflows

Ruoling Qi, Xuaner Wu, Penghang Liu +2

Agent revisions expose a fundamental correctness--efficiency trade-off during concurrent execution. Discarding ongoing work preserves latest-version correctness but wastes progress…

cs.AI2026

LinearKV: One Cached State Suffices for Position-Independent Caching in Hybrid LLMs

Yirui Liu, Ruoling Qi, Longwen Wang +5

LLM serving is increasingly accelerated by position-independent caching (PIC). Existing PIC methods, however, are built for full-attention models, where a token-indexed KV cache un…

cs.AI2026

PRTS: A Primitive Reasoning and Tasking System via Contrastive Representations

Yang Zhang, Jiangyuan Zhao, Chenyou Fan +11

Vision-Language-Action (VLA) models advance robotic control via strong visual-linguistic priors. However, existing VLAs predominantly frame pretraining as supervised behavior cloni…