| Self-refine: Iterative refinement with self-feedback A Madaan, N Tandon, P Gupta, S Hallinan, L Gao, S Wiegreffe, U Alon, ... NeurIPS '2023, 2023 | 2991 | 2023 |
| How Attentive are Graph Attention Networks? S Brody, U Alon, E Yahav International Conference on Learning Representations (ICLR) '2022, 2022 | 2365 | 2022 |
| code2vec: Learning Distributed Representations of Code U Alon, M Zilberstein, O Levy, E Yahav Principles of Programming Languages (POPL) (ACM SIGPLAN Research Highlight), 2019 | 1739 | 2019 |
| Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities G Comanici, E Bieber, M Schaekermann, I Pasupat, N Sachdeva, I Dhillon, ... arXiv preprint arXiv:2507.06261, 2025 | 1337 | 2025 |
| PAL: Program-aided Language Models L Gao, A Madaan, S Zhou, U Alon, P Liu, Y Yang, J Callan, G Neubig ICML '2023, 2023 | 1301 | 2023 |
| On the Bottleneck of Graph Neural Networks and its Practical Implications U Alon, E Yahav International Conference on Learning Representations (ICLR) '2021, 2021 | 1230 | 2021 |
| code2seq: Generating sequences from structured representations of code U Alon, S Brody, O Levy, E Yahav International Conference on Learning Representations (ICLR) '2019, 2019 | 1007 | 2019 |
| A Systematic Evaluation of Large Language Models of Code FF Xu, U Alon, G Neubig, VJ Hellendoorn MAPS 2022 & Deep Learning for Code workshop, 2022 | 982 | 2022 |
| Webarena: A realistic web environment for building autonomous agents S Zhou, FF Xu, H Zhu, X Zhou, R Lo, A Sridhar, X Cheng, Y Bisk, D Fried, ... ICLR '2024, 2023 | 721 | 2023 |
| A General Path-Based Representation for Predicting Program Properties U Alon, M Zilberstein, O Levy, E Yahav Programming Languages Design and Implementation (PLDI) '2018, 2018 | 293 | 2018 |
| Language Models of Code are Few-Shot Commonsense Learners A Madaan, S Zhou, U Alon, Y Yang, G Neubig EMNLP '2022, 2022 | 252 | 2022 |
| DocPrompting: Generating Code by Retrieving the Docs S Zhou, U Alon, FF Xu, Z Wang, Z Jiang, G Neubig International Conference on Learning Representations (ICLR) '2023 (Spotlight), 2023 | 248 | 2023 |
| Lingvo: a modular and scalable framework for sequence-to-sequence modeling J Shen, P Nguyen, Y Wu, Z Chen, MX Chen, Y Jia, A Kannan, T Sainath, ... arXiv preprint arXiv:1902.08295, 2019 | 220 | 2019 |
| Adversarial Examples for Models of Code N Yefet, U Alon, E Yahav OOPSLA 2020, 2020 | 215 | 2020 |
| Universal self-consistency for large language model generation X Chen, R Aksitov, U Alon, J Ren, K Xiao, P Yin, S Prakash, C Sutton, ... arXiv preprint arXiv:2311.17311, 2023 | 198 | 2023 |
| Learning performance-improving code edits A Madaan, A Shypula, U Alon, M Hashemi, P Ranganathan, Y Yang, ... ICLR '2024, 2023 | 193* | 2023 |
| Codebertscore: Evaluating code generation with pretrained models of code S Zhou, U Alon, S Agarwal, G Neubig EMNLP '2023, 2023 | 188 | 2023 |
| Unlimiformer: Long-range transformers with unlimited length input A Bertsch, U Alon, G Neubig, MR Gormley NeurIPS '2023, 2023 | 175 | 2023 |
| Structural Language Models of Code U Alon, R Sadaka, O Levy, E Yahav International Conference on Machine Learning (ICML) '2020, 2020 | 168* | 2020 |
| Neural Reverse Engineering of Stripped Binaries using Augmented Control Flow Graphs Y David, U Alon, E Yahav OOPSLA 2020, 2020 | 146* | 2020 |
Eran YahavTechnion, IsraelVerified email at cs.technion.ac.il
