--- title: "Miltiadis Allamanis — author profile and papers in our library" description: "Miltiadis Allamanis: 5 papers on Elamur Research (2016–2020), h-index 28 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/miltiadis-allamanis/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/miltiadis-allamanis/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Miltiadis Allamanis # Miltiadis Allamanis Miltiadis Allamanis has 5 papers in our library, in 2016–2020, most of them on [Code & programming languages](https://md.research.elamur.ai/free/en/topics/code-and-programming/), [Summarization](https://md.research.elamur.ai/free/en/topics/summarization/); often with [Charles Sutton](https://md.research.elamur.ai/free/en/authors/charles-sutton/), [Marc Brockschmidt](https://md.research.elamur.ai/free/en/authors/marc-brockschmidt/), [Hao Peng](https://md.research.elamur.ai/free/en/authors/hao-peng/). 5 papers in our library · 2016–2020 [OpenAlex](https://openalex.org/A5080221214) · [ORCID](https://orcid.org/0000-0002-5819-9900) · [Wikidata](https://www.wikidata.org/wiki/Q130850040) · [**h-index 28**](https://openalex.org/authors/A5080221214) · [80 works](https://openalex.org/works?filter=author.id:A5080221214) · [5,081 citations](https://openalex.org/works?filter=author.id:A5080221214&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/miltiadis-allamanis/#papers) · [🔗 Cited 2,877 times in our library](https://md.research.elamur.ai/free/en/authors/miltiadis-allamanis/cited-by/) · [8 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #2046](https://md.research.elamur.ai/free/en/paper-stars/page/21/#star-2046) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Miltiadis+Allamanis) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Miltiadis+Allamanis) · [dblp](https://dblp.org/search?q=Miltiadis+Allamanis) · [ACL Anthology](https://aclanthology.org/search/?q=Miltiadis+Allamanis) ## Affiliations [🏢**Microsoft Research** Cambridge · United Kingdom 2016–2023 · 21 papers](https://md.research.elamur.ai/free/en/companies/microsoft-research-united-kingdom/) · [🏢**Microsoft** Redmond · United States 2017–2022 · 17 papers](https://md.research.elamur.ai/free/en/companies/microsoft/) · [🎓**University of Edinburgh** Edinburgh · United Kingdom 2013–2021 · 13 papers](https://md.research.elamur.ai/free/en/universities/university-of-edinburgh/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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 8 The field of science this work belongs to (OpenAlex fields).[Computer Science · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Information Systems · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Software · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/software/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Science Applications · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-science-applications/) 🧭 Topics 2 Research subjects and languages the work is about.[Code & programming languages · 2 works](https://md.research.elamur.ai/free/en/topics/code-and-programming/) · [Summarization · 1 work](https://md.research.elamur.ai/free/en/topics/summarization/) ## Works by year ### 2020s [**2020** 1 paper](https://md.research.elamur.ai/free/en/authors/miltiadis-allamanis/year/2020/) ### 2010s [**2018** 1 paper](https://md.research.elamur.ai/free/en/authors/miltiadis-allamanis/year/2018/) · [**2017** 2 papers](https://md.research.elamur.ai/free/en/authors/miltiadis-allamanis/year/2017/) · [**2016** 1 paper](https://md.research.elamur.ai/free/en/authors/miltiadis-allamanis/year/2016/) ## Papers The most cited first (OpenAlex and our library). 1. **[CodeSearchNet Challenge: Evaluating the State of Semantic Code Search](https://md.research.elamur.ai/free/en/papers/husain-2020-codesearchnet-challenge-evaluating-state-semantic/)** *(2020 · 656 citations)* Finding code from a natural-language request is difficult. Programmers name things with terse, technical identifiers, while queries describe intent loosely, so the two often share few words. The field also lacked a sizeable benchmark built for this task. The authors address both gaps with two resources. 2. **[The Adverse Effects of Code Duplication in Machine Learning Models of Code](https://md.research.elamur.ai/free/en/papers/allamanis-2018-adverse-effects-code-duplication-machine/)** *(2018 · 319 citations)* The paper studies how code duplication in large corpora (primarily those collected from GitHub) distorts the training and evaluation of machine learning models for code in the "big code" field. 3. **[A Convolutional Attention Network for Extreme Summarization of Source Code](https://md.research.elamur.ai/free/en/papers/allamanis-2016-convolutional-attention-network-extreme-summarization/)** *(2016 · 198 citations)* The authors study "extreme" summarization of source code. The model receives only the tokens of a code snippet, such as the body of a Java method, and must generate a short, meaningful name that resembles a function name. Earlier approaches depended on predefined features, such as the signature or the class. This… 4. **[A Survey of Machine Learning for Big Code and Naturalness](https://md.research.elamur.ai/free/en/papers/allamanis-2017-survey-machine-learning-big-code/)** *(2017 · 167 citations)* This survey maps out a young field that applies machine learning to source code. It is framed by the "naturalness hypothesis": code is written by people for people, so large code corpora show statistical regularities similar to those in natural language, and tools can exploit them. The authors (Microsoft Research… 5. **[Learning to Represent Programs with Graphs](https://md.research.elamur.ai/free/en/papers/allamanis-2017-learning-represent-programs-graphs/)** *(2017 · 127 citations)* The authors argue that most neural networks for code analysis treat code like ordinary text, either as a sequence of tokens or as a syntax tree. ## All works 13 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them. 1. [**CodeSearchNet Challenge: Evaluating the State of Semantic Code Search arXiv:1909.09436**Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, et al.*2020 · 656 citations*](https://md.research.elamur.ai/free/en/papers/husain-2020-codesearchnet-challenge-evaluating-state-semantic/) 2. [**The Adverse Effects of Code Duplication in Machine Learning Models of Code arXiv:1812.06469**Miltiadis Allamanis*2018 · 319 citations*](https://md.research.elamur.ai/free/en/papers/allamanis-2018-adverse-effects-code-duplication-machine/) 3. [**A Convolutional Attention Network for Extreme Summarization of Source Code arXiv:1602.03001**Miltiadis Allamanis, Hao Peng, Charles Sutton*2016 · 198 citations*](https://md.research.elamur.ai/free/en/papers/allamanis-2016-convolutional-attention-network-extreme-summarization/) 4. **[Mining Idioms from Source Code ↗](https://doi.org/10.1145/2635868.2635901) arXiv:1404.0417 · no summary yet**Miltiadis Allamanis, Charles Sutton*2014 · 180 citations* 5. **[Bimodal Modelling of Source Code and Natural Language ↗](https://proceedings.mlr.press/v37/) ICML 2015, PMLR 37:2123–2132 · no summary yet**Miltos Allamanis et al.*2015 · 179 citations* 6. **[A Survey of Machine Learning for Big Code and Naturalness](https://md.research.elamur.ai/free/en/papers/allamanis-2017-survey-machine-learning-big-code/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, et al.*2017 · 167 citations* 7. [**Learning to Represent Programs with Graphs arXiv:1711.00740**Miltiadis Allamanis, Marc Brockschmidt, Mahmoud Khademi*2017 · 127 citations*](https://md.research.elamur.ai/free/en/papers/allamanis-2017-learning-represent-programs-graphs/) 8. **[DIRE: A Neural Approach to Decompiled Identifier Naming ↗](https://doi.org/10.1109/ase.2019.00064) IEEE/ACM International Conference on Automated Software Engineering (ASE) · no summary yet**Jeremy Lacomis et al.*2019 · 102 citations* 9. **[Learning to Represent Edits ↗](https://arxiv.org/abs/1810.13337) arXiv:1810.13337 · no summary yet**Pengcheng Yin et al.*2018 · 91 citations* 10. **[Learning Continuous Semantic Representations of Symbolic Expressions ↗](https://arxiv.org/abs/1611.01423) arXiv:1611.01423 · no summary yet**Miltiadis Allamanis et al.*2016 · 57 citations* 11. **[Self-Supervised Bug Detection and Repair ↗](https://arxiv.org/abs/2105.12787) arXiv:2105.12787 · no summary yet**Miltiadis Allamanis, Henry Jackson-Flux, Marc Brockschmidt*2021 · 50 citations* 12. **[NExT: Teaching Large Language Models to Reason about Code Execution ↗](https://arxiv.org/abs/2404.14662) arXiv:2404.14662 · no summary yet**Ansong Ni et al.*2024 · 30 citations* 13. **[Modelling Natural Language, Programs, and their Intersection ↗](https://aclanthology.org/N18-6001/) Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorial Abstracts · no summary yet**Graham Neubig, Miltiadis Allamanis*2018 · 4 citations* ## Co-authors here 4 co-authors with a page, the most papers together first. - [Charles Sutton](https://md.research.elamur.ai/free/en/authors/charles-sutton/) ×2 - [Marc Brockschmidt](https://md.research.elamur.ai/free/en/authors/marc-brockschmidt/) ×2 - [Hao Peng](https://md.research.elamur.ai/free/en/authors/hao-peng/) - [Mahmoud Khademi](https://md.research.elamur.ai/free/en/authors/mahmoud-khademi/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/): [ACM Computing Surveys 2017](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/2017/) - ICML 2015, PMLR 37:2123–2132 - IEEE/ACM International Conference on Automated Software Engineering (ASE) - Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorial Abstracts ## Cited by Papers of our library cite their works 2,877 times (of the 149,439 papers whose bibliographies we read); [659 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/miltiadis-allamanis/cited-by/). Updated 2 November 2026