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Chaojun Wang

Chaojun Wang has 2 papers in our library, in 2020–2024, most of them on Machine translation, Language models & pretraining; often with Dongdong Zhang, Haoran Li, Haoyang Huang.

2 papers in our library · 2020–2024

OpenAlex · ORCID · h-index 42 · 229 works · 5,987 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 149 times in our library · ⭐ Paper Stars ranking: #5786

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

🎓Beijing Jiaotong UniversityBeijing · China2012–2026 · 51 paperscurrent🏛️Chinese Academy of SciencesBeijing · China2020–2026 · 3 paperscurrent🏢Alibaba DAMO AcademyHangzhou · China2026 · 1 papercurrent🎓Jiangnan UniversityWuxi · China2026 · 1 papercurrent🔬Ningbo Institute of Industrial TechnologyNingbo · China2026 · 1 papercurrent🎓The University of SydneySydney · Australia2017–2023 · 24 papers🎓Zhoukou Normal UniversityZhoukou · China2007–2025 · 17 papers🎓University of PennsylvaniaPhiladelphia · United States2016–2025 · 12 papers🎓Zhejiang UniversityHangzhou · China2020–2023 · 6 papers🎓Beijing University of Chemical TechnologyBeijing · China2021–2025 · 5 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 51 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 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 2Research subjects and languages the work is about.Machine translation · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20241 paper20201 paper

 Papers

The most cited first (OpenAlex and our library).

  1. On Exposure Bias, Hallucination and Domain Shift in Neural Machine Translation (2020 · 206 citations)
    This paper asks whether exposure bias actually hurts neural machine translation in practice. Exposure bias is the mismatch between teacher-forced MLE training and decoding from the model's own outputs. The authors argue it helps explain two known failures under domain shift: hallucinations (fluent output unrelated to…
  2. Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models (2024 · 65 citations)
    Instruction-tuning data for LLMs is usually derived from seed prompts or existing datasets (FLAN, Self-Instruct, Evol-Instruct), so its topical range is limited by those starting points.

 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 149 times (of the 149,439 papers whose bibliographies we read); 35 citing papers with a page here →.

Updated

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