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Yongjing Yin

Yongjing Yin has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Dialogue systems, Evaluation & benchmarks; often with Tong Xiao, Bei Li, Jingang Wang.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 13 · 51 works · 602 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 93 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #9726

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

🏢MeituanBeijing · China2026 · 7 paperscurrent🎓Westlake UniversityHangzhou · China2020–2025 · 21 papersEducation 2020–2024 · Phd🎓Zhejiang UniversityHangzhou · China2011–2024 · 17 papersEducation 2020–2024 · Phd🎓Xiamen UniversityXiamen · China2018–2023 · 13 papersEducation🎓Zhejiang University of Science and TechnologyHangzhou · China2022–2024 · 4 papers🏢TencentShenzhen · China2023–2024 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 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).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 4Research subjects and languages the work is about.Language models & pretraining · 1 workDialogue systems · 1 workEvaluation & benchmarks · 1 workInformation retrieval & search · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Lost in Literalism: How Supervised Training Shapes Translationese in LLMs (2025 · 12 citations)
    LLMs learn from huge amounts of native text, yet their translations often still sound overly literal. The authors examine this "translationese" in LLM-based machine translation and trace it to supervised fine-tuning (SFT). Professional translators marked literal or unnatural spans in English-Chinese and…
  2. MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval Benchmarks (2026)
    Conversational retrieval decides which evidence a RAG system can use, but its benchmarks have two kinds of flaws.

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 Novel Graph-based Multi-modal Fusion Encoder for Neural Machine Translation ↗Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yetYongjing Yin et al.2020 · 192 citations
  2. Multi-Domain Neural Machine Translation with Word-Level Domain Context Discrimination ↗Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yetJiali Zeng et al.2018 · 103 citations
  3. Lost in Literalism: How Supervised Training Shapes Translationese in LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Yafu Li, Ronghao Zhang, Zhilin Wang, et al.2025 · 12 citations
  4. MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval BenchmarksAnnual Meeting of the Association for Computational Linguistics (ACL)Junhao Ruan, Abudukeyumu Abudula, Bei Li, et al.2026

 Co-authors here

12 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 93 times (of the 149,439 papers whose bibliographies we read); 9 citing papers with a page here →.

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