3 papers
cs.LG2026
PrefillShare: A Shared Prefill Module for KV Reuse in Multi-LLM Disaggregated Serving
Sunghyeon Woo, Hoseung Kim, Sunghwan Shim +8
Multi-agent systems increasingly orchestrate multiple specialized language models to solve complex real-world problems, often invoking them over a shared context. This execution pa…
cs.CL2026
Training-free Dropout Sampling for Semantic Token Acceptance in Speculative Decoding
Jeongtae Lee, Minjung Jo, Hyunjoon Jeong +5
Speculative decoding accelerates large language model inference by proposing tokens with a lightweight draft model and selectively accepting them using a target model. This work in…
cs.LG2025
DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation
Sunghyeon Woo, Baeseong Park, Byeongwook Kim +4
Large language models (LLMs) have achieved significant success across various domains. However, training these LLMs typically involves substantial memory and computational costs du…