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Muyun Yang

Muyun Yang has 3 papers in our library, in 2025, most of them on Evaluation & benchmarks, Efficient models & compression; often with Tiejun Zhao, Conghui Zhu, Bing Xu.

3 papers in our library · 2025

OpenAlex · ORCID · Wikidata · h-index 14 · 175 works · 858 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 107 times in our library · 9 more in our library without a page yet · ⭐ Paper Stars ranking: #8304

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 · China1920–2026 · 140 papersEducationEmployment since 1920current🎓Harbin Engineering UniversityHarbin · China2006–2009 · 6 papers🎓The University of OsakaOsaka · Japan2024–2025 · 2 papers🏢Microsoft Research AsiaBeijing · China2016–2021 · 2 papers🎓Heilongjiang Institute of TechnologyHarbin · China2009–2011 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 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 · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 2Research subjects and languages the work is about.Evaluation & benchmarks · 1 workEfficient models & compression · 1 work

 Works by year

2020s

20253 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Benchmarking LLMs for Translating Classical Chinese Poetry: Evaluating Adequacy, Fluency, and Elegance (2025 · 18 citations)
    The paper asks whether current LLMs can translate in a way that is accurate, natural, and aesthetically refined.
  2. LoRA-drop: Efficient LoRA Parameter Pruning based on Output Evaluation (2025 · 12 citations)
    LoRA lowers the cost of fine-tuning. For billion-parameter models, though, its trainable weights still need considerable compute. Storage also adds up when providers keep a separate adapter for each user. Earlier pruning methods (Sparse Adapter, AdaLoRA, SoRA) rank adapter importance using only properties of the…
  3. MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive Training (2025 · 4 citations)
    Large language models often fail on instructions that combine many constraints, frequently dropping some of them.

All works

12 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. Hierarchical Recurrent Neural Network for Document Modeling ↗Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing · no summary yetRui Lin et al.2015 · 192 citations
  2. Benchmarking LLMs for Translating Classical Chinese Poetry: Evaluating Adequacy, Fluency, and EleganceConference on Empirical Methods in Natural Language Processing (EMNLP)Andong Chen, Lianzhang Lou, Kehai Chen, et al.2025 · 18 citations
  3. All in Strings: a Powerful String-based Automatic MT Evaluation Metric with Multiple Granularities ↗Coling 2010: Posters · no summary yetJunguo Zhu et al.2010 · 16 citations
  4. Evaluating o1-Like LLMs: Unlocking Reasoning for Translation through Comprehensive Analysis ↗arXiv:2502.11544 · no summary yetAndong Chen et al.2025 · 14 citations
  5. LoRA-drop: Efficient LoRA Parameter Pruning based on Output EvaluationInternational Conference on Computational Linguistics (COLING)Hongyun Zhou, Xiangyu Lu, Wang Xu, et al.2025 · 12 citations
  6. Large Language Models for Classical Chinese Poetry Translation: Benchmarking, Evaluating, and Improving ↗arXiv:2408.09945 · no summary yetAndong Chen et al.2024 · 11 citations
  7. Legal Fact Prediction: The Missing Piece in Legal Judgment Prediction ↗Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing · no summary yetJunkai Liu et al.2025 · 8 citations
  8. Improving Translation Quality Estimation with Bias Mitigation ↗Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetHui Huang et al.2023 · 5 citations
  9. A Statistical Machine Translation Model Based on a Synthetic Synchronous Grammar ↗Proceedings of the ACL-IJCNLP 2009 Conference Short Papers · no summary yetHongfei Jiang et al.2009 · 5 citations
  10. MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive TrainingAnnual Meeting of the Association for Computational Linguistics (ACL)Hui Huang, Jiaheng Liu, Yancheng He, et al.2025 · 4 citations
  11. References Extension for the Automatic Evaluation of MT by Syntactic Hybridization ↗Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation (SSST-3) at NAACL HLT 2009 · no summary yetBo Wang et al.2009 · 1 citation
  12. A Study of Translation Rule Classification for Syntax-based Statistical Machine Translation ↗Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation (SSST-3) at NAACL HLT 2009 · no summary yetHongfei Jiang et al.2009

 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 107 times (of the 149,439 papers whose bibliographies we read); 20 citing papers with a page here →.

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