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Jiaxiang Liu

Jiaxiang Liu has 2 papers in our library, in 2021, most of them on Language models & pretraining; often with Chao Pang, Junyuan Shang, Shikun Feng.

2 papers in our library · 2021

OpenAlex · ORCID · h-index 18 · 71 works · 1,285 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 173 times in our library · ⭐ Paper Stars ranking: #4387

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

🎓Northwestern Polytechnical UniversityXi'an · China2023–2026 · 9 paperscurrent🏢BaiduBeijing · China2019–2025 · 14 papers🎓Beihang UniversityBeijing · China2018–2023 · 10 papers🎓Zhejiang UniversityHangzhou · China2024–2025 · 5 papers🎓Shenzhen UniversityShenzhen · China2022–2023 · 5 papers🎓University of WaterlooWaterloo · Canada2021–2022 · 3 papers🎓Wuhan University of Science and TechnologyWuhan · China2016–2017 · 3 papers🏛️Chinese Academy of SciencesBeijing · China2025 · 2 papers🎓Columbia UniversityNew York · United States2023 · 2 papers🎓Tsinghua UniversityBeijing · China2016 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 10 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 · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 2 works

 Works by year

2020s

20212 papers

 Papers

The most cited first (OpenAlex and our library).

  1. ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation (2021 · 332 citations)
    Most very large language models, such as GPT-3, learn only from raw text and are trained auto-regressively.
  2. ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and Generation (2021 · 63 citations)
    Very large language models such as GPT-3 show that scale pays off. However, most are trained on plain text only, and their outputs are hard to steer or verify against real-world facts. This work scales up the knowledge-enhanced ERNIE 3.0 framework, which combines auto-encoding and auto-regressive networks and learns…

 Co-authors here

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

 Cited by

Papers of our library cite their works 173 times (of the 149,439 papers whose bibliographies we read); 29 citing papers with a page here →.

Updated

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