Author

Baeseong Park

3 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#machine learning Feb 2026

PrefillShare: A Shared Prefill Module for KV Reuse in Multi-LLM Disaggregated Serving

This work proposes PrefillShare, a novel algorithm that enables sharing the prefill stage across multiple fine-tuned models in a disaggregated setting and introduces a routing mechanism that enables effective prefill sharing in a vLLM-based disaggregated system.

Sunghyeon Woo, Hoseung Kim, S. Shim et al. · arXiv.org · 3 citations

#artificial intelligence Preprint Sep 2026

SlimWise: Decoupling Expert Pruning Across Prefill and Decode for Efficient MoE Serving

SlimWise is presented, a serving framework that tailors the expert pool to each inference phase that improves decode throughput by up to 1.81x at 50% expert pruning with minimal accuracy loss and shows that benchmark accuracy can conceal substantial pruning-induced changes in generation length.

Gunho Park, Kyoungho Jeun, Juntaek Oh et al. · 0 citations

#artificial intelligence Preprint Sep 2026

BV Loss: Block Verification-Aware Loss for Block Diffusion Speculative Decoding

Block Verification-aware loss (BV loss), a training objective designed to maximize the expected acceptance length of a drafted sequence, outperforms tokenwise acceptance objectives such as TV loss and LK loss, and its gains extend to token verification and greedy decoding.

Suyoung Kim, Jahyun Koo, Hyeonjin Kim et al. · 0 citations