---
title: "Who cites Eran Yahav — 230 papers of our library"
description: "230 papers of the Elamur Research library cite the works of Eran Yahav, found in their bibliographies; the most cited first."
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---
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# Who cites Eran Yahav

291 citations of their works from 230 papers of our library (of the 149,439 whose bibliographies we read) · 43 with a page here, the most cited first · [← Eran Yahav](https://md.research.elamur.ai/free/en/authors/eran-yahav/)

1. **[CodeBERT: A Pre-Trained Model for Programming and Natural Languages](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhangyin Feng, Daya Guo, Duyu Tang, et al.*2020 · 2,967 citations*
2. [**Evaluating Large Language Models Trained on Code arXiv:2107.03374**Mark Chen, Jerry Tworek, Heewoo Jun, et al.*2021 · 2,659 citations*](https://md.research.elamur.ai/free/en/papers/chen-2021-evaluating-large-language-models-trained/)
3. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
4. [**Program Synthesis with Large Language Models arXiv:2108.07732**Jacob Austin, Augustus Odena, Maxwell Nye, et al.*2021 · 1,192 citations*](https://md.research.elamur.ai/free/en/papers/austin-2021-program-synthesis-large-language-models/)
5. **[Unified Pre-training for Program Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ahmad-2021-unified-pre-training-program-understanding/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al.*2021 · 750 citations*
6. **[Analysis Methods in Neural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/belinkov-2019-analysis-methods-neural-language-processing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yonatan Belinkov, James Glass*2019 · 740 citations*
7. [**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/)
8. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
9. **[Do NLP Models Know Numbers? Probing Numeracy in Embeddings](https://md.research.elamur.ai/free/en/papers/wallace-2019-do-nlp-models-know-numbers/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eric Wallace, Yizhong Wang, Sujian Li, et al.*2019 · 352 citations*
10. [**GraphCodeBERT: Pre-training Code Representations with Data Flow arXiv:2009.08366**Daya Guo, Shuo Ren, Shuai Lu, et al.*2021 · 332 citations*](https://md.research.elamur.ai/free/en/papers/guo-2021-graphcodebert-pre-training-code-representations/)
11. [**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/)
12. [**Compositionality decomposed: how do neural networks generalise? arXiv:1908.08351**Dieuwke Hupkes, Verna Dankers, Mathijs Mul, et al.*2019 · 162 citations*](https://md.research.elamur.ai/free/en/papers/hupkes-2019-compositionality-decomposed-neural-networks-generalise/)
13. [**Unsupervised Translation of Programming Languages arXiv:2006.03511**Marie-Anne Lachaux, Baptiste Roziere, Lowik Chanussot, et al.*2020 · 160 citations*](https://md.research.elamur.ai/free/en/papers/lachaux-2020-unsupervised-translation-programming-languages/)
14. **[PyMT5: multi-mode translation of natural language and Python code with transformers](https://md.research.elamur.ai/free/en/papers/clement-2020-pymt5-multi-mode-translation-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Colin Clement, Dawn Drain, Jonathan Timcheck, et al.*2020 · 158 citations*
15. **[TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation](https://md.research.elamur.ai/free/en/papers/uchendu-2021-turingbench-benchmark-environment-turing-test/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adaku Uchendu, Zeyu Ma, Thai Le, et al.*2021 · 140 citations*
16. [**A Systematic Evaluation of Large Language Models of Code arXiv:2202.13169**Frank F. Xu, Uri Alon, Graham Neubig, et al.*2022 · 125 citations*](https://md.research.elamur.ai/free/en/papers/xu-2022-systematic-evaluation-large-language-models/)
17. **[ReACC: A Retrieval-Augmented Code Completion Framework](https://md.research.elamur.ai/free/en/papers/lu-2022-reacc-retrieval-augmented-code-completion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuai Lu, Nan Duan, Hojae Han, et al.*2022 · 125 citations*
18. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
19. **[On the Ability and Limitations of Transformers to Recognize Formal Languages](https://md.research.elamur.ai/free/en/papers/bhattamishra-2020-ability-limitations-transformers-recognize-formal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Satwik Bhattamishra, Kabir Ahuja, Navin Goyal*2020 · 113 citations*
20. [**Neural Networks and the Chomsky Hierarchy arXiv:2207.02098**Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, et al.*2022 · 112 citations*](https://md.research.elamur.ai/free/en/papers/deletang-2022-neural-networks-chomsky-hierarchy/)
21. [**Learning to Prove Theorems via Interacting with Proof Assistants arXiv:1905.09381**Kaiyu Yang, Jia Deng*2019 · 90 citations*](https://md.research.elamur.ai/free/en/papers/yang-2019-learning-prove-theorems-interacting-proof/)
22. [**LSTM Networks Can Perform Dynamic Counting Proceedings of the Workshop on Deep Learning and Formal Languages: Building Bridges**Mirac Suzgun, Yonatan Belinkov, Stuart Shieber, et al.*2019 · 89 citations*](https://md.research.elamur.ai/free/en/papers/suzgun-2019-lstm-networks-can-perform-dynamic/)
23. [**code2seq: Generating Sequences from Structured Representations of Code arXiv:1808.01400**Uri Alon, Shaked Brody, Omer Levy, et al.*2018 · 72 citations*](https://md.research.elamur.ai/free/en/papers/alon-2018-code2seq-generating-sequences-structured-representations/)
24. **[Mission: Impossible Language Models](https://md.research.elamur.ai/free/en/papers/kallini-2024-mission-impossible-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Julie Kallini, Isabel Papadimitriou, Richard Futrell, et al.*2024 · 70 citations*
25. **[RNNs can generate bounded hierarchical languages with optimal memory](https://md.research.elamur.ai/free/en/papers/hewitt-2020-rnns-can-generate-bounded-hierarchical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**John Hewitt, Michael Hahn, Surya Ganguli, et al.*2020 · 65 citations*
26. [**PanGu-Coder: Program Synthesis with Function-Level Language Modeling arXiv:2207.11280**Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta, et al.*2022 · 49 citations*](https://md.research.elamur.ai/free/en/papers/christopoulou-2022-pangu-coder-program-synthesis/)
27. **[Closing Brackets with Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/skachkova-2018-closing-brackets-recurrent-neural-networks/) [EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/emnlp-workshop-blackboxnlp-analyzing-and-interpreting-neural-networks-for-nlp/)**Natalia Skachkova, Thomas Trost, Dietrich Klakow*2018 · 43 citations*
28. **[How Can Self-Attention Networks Recognize Dyck-n Languages?](https://md.research.elamur.ai/free/en/papers/ebrahimi-2020-how-can-self-attention-networks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Javid Ebrahimi, Dhruv Gelda, Wei Zhang*2020 · 41 citations*
29. **[Jump to better conclusions: SCAN both left and right](https://md.research.elamur.ai/free/en/papers/bastings-2018-jump-better-conclusions-scan-both/) [EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/emnlp-workshop-blackboxnlp-analyzing-and-interpreting-neural-networks-for-nlp/)**Jasmijn Bastings, Marco Baroni, Jason Weston, et al.*2018 · 38 citations*
30. **[Exploring Transitivity in Neural NLI Models through Veridicality](https://md.research.elamur.ai/free/en/papers/yanaka-2021-exploring-transitivity-neural-nli-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hitomi Yanaka, Koji Mineshima, Kentaro Inui*2021 · 27 citations*
31. [**Memory Augmented Large Language Models are Computationally Universal arXiv:2301.04589**Dale Schuurmans*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/schuurmans-2023-memory-augmented-large-language-models/)
32. **[Targeted Syntactic Evaluation on the Chomsky Hierarchy](https://md.research.elamur.ai/free/en/papers/someya-2024-targeted-syntactic-evaluation-chomsky-hierarchy/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Taiga Someya, Ryo Yoshida, Yohei Oseki*2024 · 10 citations*
33. **[Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic Biases](https://md.research.elamur.ai/free/en/papers/hu-2025-between-circuits-chomsky-pre-pretraining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael Y. Hu, Jackson Petty, Chuan Shi, et al.*2025 · 9 citations*
34. [**Stable Code Technical Report arXiv:2404.01226**Nikhil Pinnaparaju, Reshinth Adithyan, Duy Phung, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/pinnaparaju-2024-stable-code-technical-report/)
35. **[TArC: Tunisian Arabish Corpus, First complete release](https://md.research.elamur.ai/free/en/papers/gugliotta-2022-tarc-tunisian-arabish-corpus-first/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Elisa Gugliotta, Marco Dinarelli*2022 · 8 citations*
36. **[TreeDiff: AST-Guided Code Generation with Diffusion LLMs](https://md.research.elamur.ai/free/en/papers/zeng-2026-treediff-ast-guided-code-generation/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Yiming Zeng, Jinghan Cao, Zexin Li, et al.*2026 · 3 citations*
37. **[LATE-IIMAS at Semeval-2026 Task 13: Evaluating GNNs, PLMs, LLMs, and Stylometry for Automatic Code Identification](https://md.research.elamur.ai/free/en/papers/valdez-2026-late-iimas-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Andric Valdez, Emmanuel Ancona, Sebastián Bernardino, et al.*2026 · 1 citation*
38. **[Research Progress of Pre-trained Model in Software Engineering (预训练模型在软件工程领域应用研究进展)](https://md.research.elamur.ai/free/en/papers/gong-2024-pre-trained-model/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Lina Gong (宫丽娜), Yiren Zhou (周易人), Yu Qiao (乔羽), et al.*2024 · 1 citation*
39. **[An Empirical Analysis of Task Relations in the Multi-Task Annotation of an Arabizi Corpus](https://md.research.elamur.ai/free/en/papers/gugliotta-2023-empirical-analysis-task-relations-multi/) [Conference on Language, Data and Knowledge](https://md.research.elamur.ai/free/en/venues/ldk/)**Elisa Gugliotta, Marco Dinarelli*2023 · 1 citation*
40. **[Do Transformers Grok Succinct Algorithms? Mechanistic Evidence for Counting Circuits](https://md.research.elamur.ai/free/en/papers/zhao-2026-do-transformers-grok-succinct-algorithms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yizheng Zhao*2026*
41. **[From Logical to Computational Sparsity: Structure-Aware Block-Sparse Attention for Long-Code Completion](https://md.research.elamur.ai/free/en/papers/wang-2026-logical-computational-sparsity-structure-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanli Wang, Yanlin Wang, Bowen Zhang, et al.*2026*
42. **[Pixel Phantoms at SemEval-2026 Task 13: Exploring Classical and Neural Approaches for AI-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/s-2026-pixel-phantoms-semeval-2026-task-2026-semeval-1-256/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Jithu Morrison S, Janani Hariharakrishnan, Angel Deborah S, et al.*2026*
43. **[The Development of Spectral and Temporal Encodings in Speech Sounds](https://md.research.elamur.ai/free/en/papers/tan-2026-development-spectral-temporal-encodings-speech/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Frank Lihui Tan, Youngah Do*2026*

187 more citing papers of our library have no page here yet.

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