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Haiyun Jiang

Haiyun Jiang has 2 papers in our library, in 2023, most of them on Language models & pretraining, Dialogue systems, Evaluation & benchmarks; often with Deng Cai, Jia Li, Longyue Wang.

2 papers in our library · 2023

OpenAlex · ORCID · h-index 20 · 79 works · 1,616 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 139 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #4693

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

🎓Hunan University of TechnologyZhuzhou · China2012–2026 · 34 paperscurrent🏢TencentShenzhen · China2022–2023 · 9 papers🎓Southeast UniversityNanjing · China2005–2009 · 7 papers🎓Nanjing Institute of TechnologyNanjing · China2005–2009 · 6 papers🔬Jiangsu Key Laboratory for Advanced Metallic MaterialsNanjing · China2009 · 4 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.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 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 3Research subjects and languages the work is about.Dialogue systems · 1 workEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20232 papersHaiyun Jiang's papers of 2023

 Papers

The most cited first (OpenAlex and our library).

  1. Exploring the Use of Large Language Models for Reference-Free Text Quality Evaluation: An Empirical Study (2023 · 113 citations)
    The paper asks whether large language models, mainly ChatGPT, can judge the quality of generated text without human-written references, and which way of prompting them works best.
  2. Large Language Models Meet Harry Potter: A Dataset for Aligning Dialogue Agents with Characters (2023 · 80 citations)
    Chat-oriented LLMs such as ChatGPT and GPT-4 can hold open-domain conversations, but they struggle to stay in character as a specific fictional person.

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. Exploring the Use of Large Language Models for Reference-Free Text Quality Evaluation: An Empirical StudyFindings of the Association for Computational LinguisticsYi Chen, Rui Wang, Haiyun Jiang, et al.2023 · 113 citations
  2. Large Language Models Meet Harry Potter: A Dataset for Aligning Dialogue Agents with CharactersFindings of the Association for Computational LinguisticsNuo Chen, Yan Wang, Haiyun Jiang, et al.2023 · 80 citations
  3. On the Evaluation Metrics for Paraphrase GenerationProceedings of the 2022 Conference on Empirical Methods in Natural Language Processing · original ↗ · no summary yetLingfeng Shen et al.2022 · 65 citations
  4. MCPG: A Flexible Multi-Level Controllable Framework for Unsupervised Paraphrase GenerationFindings of the Association for Computational Linguistics: EMNLP 2022 · original ↗ · no summary yetYi Chen et al.2022 · 10 citations

 Co-authors here

8 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 139 times (of the 141,840 papers whose bibliographies we read); 13 citing papers with a page here →.

Updated

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