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Xuefei Ning

Xuefei Ning has 2 papers in our library, in 2024–2026, most of them on Language models & pretraining, Evaluation & benchmarks, Bias, fairness & safety; often with Boxun Li, Dahua Lin, Guohao Dai.

2 papers in our library · 2024–2026

OpenAlex · ORCID · Wikidata · h-index 20 · 102 works · 1,779 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 191 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #7978

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

🎓Tsinghua UniversityBeijing · China2012–2026 · 82 papersEducation 2012–2016 · Bachelor, Electronic EngineeringEducation 2016–2021 · PhD candidate, Electronic EngineeringEmployment since 2024 · Research-Track Assistant Professor, Department of Electronic Engineeringcurrent🔬Beijing National Research Center for Information Science and TechnologyBeijing · China2018–2025 · 4 papers🏢Huawei TechnologiesShenzhen · China2022 · 2 papers
🏛️Huawei-Tsinghua Joint Post-Doctoral ProgramBeijing · China2021–2023Employment 2021–2023

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

 Fields, topics and concepts

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

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workSafety Research · 1 workSocial Sciences · 1 work

🧭 Topics 4Research subjects and languages the work is about.Evaluation & benchmarks · 1 workBias, fairness & safety · 1 workEfficient models & compression · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20261 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. LV-Eval: A Balanced Long-Context Benchmark with 5 Length Levels Up to 256K (2024 · 41 citations)
    Long-context LLMs now advertise input windows of 128k–256k tokens or more. Popular evaluation suites, however, average only about 5k–21k words. They often reuse unmodified public texts that models may have memorized, and they score answers with brittle n-gram metrics. LV-Eval addresses these gaps with a bilingual…
  2. How Quantization Shapes Bias in Large Language Models (2026 · 3 citations)
    Quantization is a common way to shrink LLMs for deployment, but its effect on social bias has received little systematic study.

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. A Survey on Efficient Inference for Large Language Models ↗arXiv:2404.14294 · no summary yetZixuan Zhou et al.2024 · 113 citations
  2. Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation ↗arXiv:2307.15337 · no summary yetXuefei Ning et al.2023 · 72 citations
  3. LV-Eval: A Balanced Long-Context Benchmark with 5 Length Levels Up to 256KarXiv:2402.05136Tao Yuan, Xuefei Ning, Dong Zhou, et al.2024 · 41 citations
  4. How Quantization Shapes Bias in Large Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Federico Marcuzzi, Xuefei Ning, Roy Schwartz, et al.2026 · 3 citations

 Co-authors here

5 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 191 times (of the 149,439 papers whose bibliographies we read); 34 citing papers with a page here →.

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