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cs.LG2026
QUOKA: Query-Oriented KV Selection For Efficient LLM Prefill
Dalton Jones, Junyoung Park, Matthew Morse +3
We present QUOKA: Query-oriented KV selection for efficient attention, a training-free and hardware agnostic sparse attention algorithm for accelerating transformer inference under…
cs.LG2026
Fast Forward: Accelerating LLM Prefill with Predictive FFN Sparsity
Aayush Gautam, Mukul Gagrani, Junyoung Park +3
The prefill stage of large language model (LLM) inference is a key computational bottleneck for long-context workloads. At short-to-moderate context lengths (1K--16K tokens), Feed-…
cs.LG2025
CAOTE: KV Cache Selection for LLMs via Attention Output Error-Based Token Eviction
Raghavv Goel, Junyoung Park, Mukul Gagrani +5
While long context support of large language models has extended their abilities, it also incurs challenges in memory and compute which becomes crucial bottlenecks in resource-rest…