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Xiaoxuan Liu

Xiaoxuan Liu has 2 papers in our library, in 2023–2024, most of them on GPU & parallel computing, Efficient models & compression; often with Ion Gabriel Stoica, Alvin Cheung, Hao Zhang.

2 papers in our library · 2023–2024

OpenAlex · ORCID · h-index 21 · 89 works · 2,192 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 156 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #8051

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

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 25 more institutions on single bylines are not listed.

 Fields, topics and concepts

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

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. Online Speculative Decoding (2023 · 65 citations)
    Speculative decoding speeds up LLM inference by having a small draft model propose tokens that a large target model checks in parallel.
  2. MoE-Lightning: High-Throughput MoE Inference on Memory-constrained GPUs (2024 · 51 citations)
    Mixture-of-Experts LLMs keep per-token compute low but need very large amounts of memory. The expert FFNs of Mixtral 8x22B alone take more than 256 GB. This paper targets offline, throughput-oriented batch inference, such as model evaluation, synthetic data generation and data wrangling, when the GPU cannot hold the…

All works

4 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Online Speculative DecodingarXiv:2310.07177Xiaoxuan Liu, Lanxiang Hu, Peter Bailis, et al.2023 · 65 citations
  2. MoE-Lightning: High-Throughput MoE Inference on Memory-constrained GPUsASPLOS 2025Shiyi Cao, Shu Liu, Tyler Griggs, et al.2024 · 51 citations
  3. Mélange: Cost Efficient Large Language Model Serving by Exploiting GPU Heterogeneity ↗arXiv:2404.14527 · no summary yetTyler Griggs et al.2024 · 26 citations
  4. TurboSpec: Closed-loop Speculation Control System for Optimizing LLM Serving Goodput ↗arXiv (Cornell University) · no summary yetXiaoxuan Liu et al.2024 · 20 citations

 Co-authors here

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

Venues

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

 Cited by

Papers of our library cite their works 156 times (of the 149,439 papers whose bibliographies we read); 18 citing papers with a page here →.

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