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Jian Jiao

Jian Jiao has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining; often with Chen Lin, Nan Duan, Weizhu Chen.

2 papers in our library · 2023–2024

OpenAlex · ORCID · h-index 27 · 325 works · 3,069 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 224 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6342

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

🎓Harbin Institute of TechnologyHarbin · China2009–2026 · 232 paperscurrent🔬Peng Cheng LaboratoryShenzhen · China2019–2026 · 103 paperscurrent🎓Changchun Normal UniversityChangchun · China2022–2026 · 5 paperscurrent🎓Xi'an Jiaotong UniversityXi'an · China2022–2026 · 3 paperscurrent🎓Beijing Information Science & Technology UniversityBeijing · China2016–2026 · 2 paperscurrent🎓Beijing Institute of Aeronautical MaterialsBeijing · China2026 · 1 papercurrent🏢MicrosoftRedmond · United States2022–2024 · 15 papers🎓Jilin UniversityChangchun · China2021–2025 · 7 papers🔬Nanjing Hydraulic Research InstituteNanjing · China2022–2024 · 4 papers🎓University of Electronic Science and Technology of ChinaChengdu · China2023–2024 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 18 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 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

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

 Works by year

2020s

20241 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators (2023 · 152 citations)
    Manually labelling data for NLP is slow and expensive. This paper asks whether GPT-3.5 models can replace crowd workers. The authors build AnnoLLM, which gives the model the same materials a human annotator would get: a task description, label definitions and labelled examples. It then adds a two-stage…
  2. Rho-1: Not All Tokens Are What You Need (2024 · 59 citations)
    Standard LLM pre-training applies the next-token loss uniformly, even though filtered corpora still contain noisy, irrelevant, or already-mastered tokens.

All works

3 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. PromptBERT: Improving BERT Sentence Embeddings with Prompts ↗Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · no summary yetTing Jiang et al.2022 · 198 citations
  2. AnnoLLM: Making Large Language Models to Be Better Crowdsourced AnnotatorsarXiv:2303.16854Xingwei He, Zhenghao Lin, Yeyun Gong, et al.2023 · 152 citations
  3. Rho-1: Not All Tokens Are What You NeedarXiv:2404.07965Zhenghao Lin, Zhibin Gou, Yeyun Gong, et al.2024 · 59 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 224 times (of the 149,439 papers whose bibliographies we read); 51 citing papers with a page here →.

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