code2vec: Learning Distributed Representations of Code U Alon, M Zilberstein, O Levy, E Yahav Principles of Programming Languages (POPL), 2019 | 245 | 2019 |
code2seq: Generating sequences from structured representations of code U Alon, S Brody, O Levy, E Yahav International Conference on Learning Representations (ICLR), 2019 | 145 | 2019 |
A General Path-Based Representation for Predicting Program Properties U Alon, M Zilberstein, O Levy, E Yahav Programming Languages Design and Implementation (PLDI), 2018 | 86 | 2018 |
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 | 71 | 2019 |
Structural Language Models of Code U Alon, R Sadaka, O Levy, E Yahav International Conference on Machine Learning (ICML) '2020, 2020 | 16* | 2020 |
On the Bottleneck of Graph Neural Networks and its Practical Implications U Alon, E Yahav International Conference on Learning Representations (ICLR) '2021, 2021 | 10 | 2021 |
Neural Reverse Engineering of Stripped Binaries using Augmented Control Flow Graphs Y David, U Alon, E Yahav OOPSLA 2020, 2020 | 8* | 2020 |
Adversarial Examples for Models of Code N Yefet, U Alon, E Yahav OOPSLA 2020, 2020 | 6 | 2020 |
Contextual Speech Recognition with Difficult Negative Training Examples U Alon, G Pundak, TN Sainath International Conference on Acoustics, Speech, and Signal Processing (ICASSP …, 2019 | 6 | 2019 |
A Structural Model for Contextual Code Changes S Brody, U Alon, E Yahav OOPSLA 2020, 2020 | 1* | 2020 |
Single-Node Attack for Fooling Graph Neural Networks B Finkelshtein, C Baskin, E Zheltonozhskii, U Alon arXiv preprint arXiv:2011.03574, 2020 | | 2020 |