Elamur Research⌕
☰
home / authors / Jie M. Zhang

Jie M. Zhang

Jie M. Zhang has 2 papers in our library, in 2024–2026, most of them on Language models & pretraining, Code & programming languages; often with Guangtao Zeng, Helen Yannakoudakis, Jianbo Dai.

2 papers in our library · 2024–2026

OpenAlex · ORCID · Wikidata · h-index 27 · 124 works · 4,645 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 43 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #9367

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

🎓King's College LondonLondon · United Kingdom2022–2026 · 96 papersEmployment since 2022 · Lecturer, Informaticscurrent🎓University College LondonLondon · United Kingdom2019–2026 · 19 papersEmployment 2019–2022 · Research Fellow, Computer Science🎓Peking UniversityBeijing · China2012–2019 · 12 papersEducation 2012–2018 · PhD, Computer Science🎓University of LondonLondon · United Kingdom2019–2026 · 4 papers🎓Nanjing UniversityNanjing · China2011–2012 · 3 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 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksInformation Systems · 2 worksLanguage and Linguistics · 2 worksComputer Science Applications · 1 work

🧭 Topics 2Research subjects and languages the work is about.Code & programming languages · 2 worksLanguage models & pretraining · 2 works

 Works by year

2020s

20261 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuning (2024 · 11 citations)
    Code-generating LLMs are usually tuned for correctness, but the programs they produce often run slower and use more memory than human-written reference solutions.
  2. A Study of LLMs' Preferences for Libraries and Programming Languages (2026 · 5 citations)
    The paper examines a rarely evaluated aspect of LLM code generation: which libraries and programming languages a model picks when the prompt leaves that choice open.

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. Leveraging Automated Unit Tests for Unsupervised Code Translation ↗arXiv:2110.06773 · no summary yetBaptiste Roziere et al.2022 · 40 citations
  2. EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuningarXiv:2410.10209Dong Huang, Guangtao Zeng, Jianbo Dai, et al.2024 · 11 citations
  3. A Study of LLMs' Preferences for Libraries and Programming LanguagesFindings of the Association for Computational LinguisticsLukas Twist, Mark Harman, Don Syme, et al.2026 · 5 citations
  4. TRACE: Evaluating Execution Efficiency of LLM-Based Code Translation ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetZhihao Gong et al.2026 · 1 citation

 Co-authors here

5 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 43 times (of the 149,439 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/jie-m-zhang/