Shengyu Liu

Shengyu Liu has 3 papers in our library, in 2023–2024, most of them on Language models & pretraining; often with Xin Jin, Xuanzhe Liu, Yinmin Zhong.

3 papers in our library · 2023–2024

The profile is the library's match of the name; two people with one name are not always told apart.

Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

Of its works in our library, with the number of works on each.

The most cited first (OpenAlex and our library).

DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving (2024 · 409 citations)
LLM inference has two phases with different profiles. Prefill processes the whole prompt in one compute-heavy step. Decoding emits one token per step and is bound by memory bandwidth. Mainstream systems batch both phases on the same GPUs. As a result, prefill delays inflate TPOT, decoding work inflates TTFT, and both…
LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence Parallelism (2024 · 131 citations)
Long-context LLMs (Claude-3, Gemini-1.5 and LWM all accept up to 1M tokens) create very uneven resource demands.
Fast Distributed Inference Serving for Large Language Models (2023 · 123 citations)
FastServe, from Peking University, is a distributed serving system for large language models that targets the latency of interactive applications.

7 co-authors with a page, the most papers together first.

Where their works here were published, the most works first, with the editions of those that have a page.

Papers of our library cite their works 568 times (of the 149,439 papers whose bibliographies we read); 22 citing papers with a page here →.

Updated 2 November 2026