Exploiting Code Symmetries for Learning Program Semantics

Exploiting Code Symmetries for Learning Program Semantics

7 August 2023

Scott Geng

Lorenzo Cavallaro

Papers citing "Exploiting Code Symmetries for Learning Program Semantics"

8 / 8 papers shown

Title
ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding Indraneil Paul Haoyi Yang Goran Glavas Kristian Kersting Iryna Gurevych AAML SyDa 34 0 0 27 Mar 2025
Large Language Models for Cyber Security: A Systematic Literature Review HanXiang Xu Shenao Wang Ningke Li K. Wang Yanjie Zhao Kai Chen Ting Yu Yang Janet Liu H. Wang 29 23 0 08 May 2024
LLM4Vuln: A Unified Evaluation Framework for Decoupling and Enhancing LLMs' Vulnerability Reasoning Yuqiang Sun Daoyuan Wu Yue Xue Han Liu Wei Ma Lyuye Zhang Miaolei Shi Yingjiu Li ELM 76 47 0 29 Jan 2024
Automatic Symmetry Discovery with Lie Algebra Convolutional Network Nima Dehmamy Robin G. Walters Yanchen Liu Dashun Wang Rose Yu AI4CE 76 81 0 15 Sep 2021
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation Yue Wang Weishi Wang Shafiq R. Joty S. Hoi 210 1,485 0 02 Sep 2021
DOBF: A Deobfuscation Pre-Training Objective for Programming Languages Baptiste Roziere Marie-Anne Lachaux Marc Szafraniec Guillaume Lample AI4CE 44 135 0 15 Feb 2021
Semantic Robustness of Models of Source Code Goutham Ramakrishnan Jordan Henkel Zi Wang Aws Albarghouthi S. Jha Thomas W. Reps SILM AAML 35 97 0 07 Feb 2020
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 231 3,230 0 24 Nov 2016