Elamur Research⌕
☰
home / authors / Zhiping Xiao

Zhiping Xiao

Zhiping Xiao has 3 papers in our library, in 2025, most of them on Language models & pretraining, Evaluation & benchmarks, Reasoning; often with Junyu Luo, Jingyang Yuan, Ming Zhang.

3 papers in our library · 2025

OpenAlex · ORCID · h-index 13 · 69 works · 1,335 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 211 times in our library · ⭐ Paper Stars ranking: #5915

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

🎓University of WashingtonSeattle · United States2024–2026 · 38 papersEmployment since 2024 · Postdoc, Computer Sciencecurrent🎓University of California, Los AngelesLos Angeles · United States2018–2025 · 12 papersEducation 2018–2024 · PhD, Computer Science DepartmentEmployment since 2024 · Visiting Scholar, Computer Science🎓Peking UniversityBeijing · China2016–2025 · 5 papers🎓University of California, BerkeleyBerkeley · United States2016–2019 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 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.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 2 works

🧭 Topics 6Research subjects and languages the work is about.Efficient models & compression · 1 workGPU & parallel computing · 1 workLanguage models & pretraining · 1 workEvaluation & benchmarks · 1 workReasoning · 1 workVision & language · 1 work

 Works by year

2020s

20253 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention (2025 · 142 citations)
    Standard softmax attention becomes the main cost in long-context language models. The authors estimate it takes 70–80% of decoding latency at 64k tokens. Earlier sparse attention methods often save compute on paper but not in wall-clock time. Many speed up only prefilling or only decoding, clash with GQA/MQA memory…
  2. FinMME: Benchmark Dataset for Financial Multi-Modal Reasoning Evaluation (2025 · 19 citations)
    FinMME addresses the lack of specialised benchmarks for testing multimodal large language models (MLLMs) on financial material, where charts are data-dense and interpretation requires expert knowledge.
  3. A Survey on Efficient Large Language Model Training: From Data-centric Perspectives (2025 · 14 citations)
    Post-training is the stage where LLMs acquire instruction following, alignment, reasoning and domain skills.

 Co-authors here

12 of 18 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 211 times (of the 149,439 papers whose bibliographies we read); 44 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/zhiping-xiao/