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On the Generalizability of Neural Program Models with respect to
  Semantic-Preserving Program Transformations
v1v2v3 (latest)

On the Generalizability of Neural Program Models with respect to Semantic-Preserving Program Transformations

Information and Software Technology (IST), 2020
31 July 2020
Md Rafiqul Islam Rabin
Nghi D. Q. Bui
Ke Wang
Yijun Yu
Lingxiao Jiang
Mohammad Amin Alipour
ArXiv (abs)PDFHTML

Papers citing "On the Generalizability of Neural Program Models with respect to Semantic-Preserving Program Transformations"

23 / 23 papers shown
NatGVD: Natural Adversarial Example Attack towards Graph-based Vulnerability Detection
NatGVD: Natural Adversarial Example Attack towards Graph-based Vulnerability Detection
Avilash Rath
Weiliang Qi
Youpeng Li
Xinda Wang
144
0
0
06 Oct 2025
An Initial Exploration of Fine-tuning Small Language Models for Smart Contract Reentrancy Vulnerability Detection
An Initial Exploration of Fine-tuning Small Language Models for Smart Contract Reentrancy Vulnerability Detection
Ignacio Mariano Andreozzi Pofcher
Joshua Ellul
172
0
0
25 May 2025
ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding
ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation GroundingInternational Conference on Learning Representations (ICLR), 2025
Indraneil Paul
Haoyi Yang
Goran Glavaš
Kristian Kersting
Iryna Gurevych
AAMLSyDa
263
3
0
27 Mar 2025
XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants
XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants
Adam Štorek
Mukur Gupta
Noopur Bhatt
Aditya Gupta
Janie Kim
Prashast Srivastava
Suman Jana
AAML
544
4
0
18 Mar 2025
Can LLMs Reason About Program Semantics? A Comprehensive Evaluation of LLMs on Formal Specification Inference
Can LLMs Reason About Program Semantics? A Comprehensive Evaluation of LLMs on Formal Specification InferenceAnnual Meeting of the Association for Computational Linguistics (ACL), 2025
Thanh Le-Cong
Bach Le
Toby Murray
LRM
298
11
0
22 Feb 2025
What can Large Language Models Capture about Code Functional Equivalence?
What can Large Language Models Capture about Code Functional Equivalence?North American Chapter of the Association for Computational Linguistics (NAACL), 2024
Nickil Maveli
Antonio Vergari
Shay B. Cohen
346
11
0
20 Aug 2024
Pitfalls in Language Models for Code Intelligence: A Taxonomy and Survey
Pitfalls in Language Models for Code Intelligence: A Taxonomy and SurveyACM Transactions on Software Engineering and Methodology (TOSEM), 2023
Xinyu She
Yue Liu
Yanjie Zhao
Yiling He
Li Li
Chakkrit Tantithamthavorn
Zhan Qin
Haoyu Wang
ELM
241
19
0
27 Oct 2023
Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in
  Code Models
Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in Code ModelsIEEE Transactions on Software Engineering (TSE), 2023
Zhou Yang
Zhipeng Zhao
Chenyu Wang
Jieke Shi
Dongsum Kim
Donggyun Han
David Lo
SILMAAMLMIACV
262
20
0
02 Oct 2023
A Study of Variable-Role-based Feature Enrichment in Neural Models of
  Code
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code
Aftab Hussain
Md Rafiqul Islam Rabin
Bowen Xu
David Lo
Mohammad Amin Alipour
199
3
0
08 Mar 2023
Toward a Theory of Causation for Interpreting Neural Code Models
Toward a Theory of Causation for Interpreting Neural Code ModelsIEEE Transactions on Software Engineering (TSE), 2023
David Nader-Palacio
Alejandro Velasco
Nathan Cooper
Á. Rodríguez
Kevin Moran
Denys Poshyvanyk
473
24
0
07 Feb 2023
Stealthy Backdoor Attack for Code Models
Stealthy Backdoor Attack for Code ModelsIEEE Transactions on Software Engineering (TSE), 2023
Zhou Yang
Bowen Xu
Jie M. Zhang
Hong Jin Kang
Jieke Shi
Junda He
David Lo
AAML
236
89
0
06 Jan 2023
Fix Bugs with Transformer through a Neural-Symbolic Edit Grammar
Fix Bugs with Transformer through a Neural-Symbolic Edit Grammar
Yaojie Hu
Xingjian Shi
Qiang Zhou
Lee Pike
KELM
163
15
0
13 Apr 2022
An Exploratory Study on Code Attention in BERT
An Exploratory Study on Code Attention in BERTIEEE International Conference on Program Comprehension (ICPC), 2022
Rishab Sharma
Fuxiang Chen
Fatemeh H. Fard
David Lo
200
33
0
05 Apr 2022
ReACC: A Retrieval-Augmented Code Completion Framework
ReACC: A Retrieval-Augmented Code Completion FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL), 2022
Shuai Lu
Nan Duan
Hojae Han
Daya Guo
Seung-won Hwang
Alexey Svyatkovskiy
228
190
0
15 Mar 2022
Extracting Label-specific Key Input Features for Neural Code
  Intelligence Models
Extracting Label-specific Key Input Features for Neural Code Intelligence Models
Md Rafiqul Islam Rabin
AAML
144
0
0
14 Feb 2022
Energy-bounded Learning for Robust Models of Code
Nghi D. Q. Bui
Yijun Yu
OODD
217
2
0
20 Dec 2021
Code2Snapshot: Using Code Snapshots for Learning Representations of
  Source Code
Code2Snapshot: Using Code Snapshots for Learning Representations of Source CodeInternational Conference on Machine Learning and Applications (ICMLA), 2021
Md Rafiqul Islam Rabin
Mohammad Amin Alipour
207
5
0
01 Nov 2021
Self-Supervised Learning to Prove Equivalence Between Straight-Line
  Programs via Rewrite Rules
Self-Supervised Learning to Prove Equivalence Between Straight-Line Programs via Rewrite Rules
Steve Kommrusch
Monperrus Martin
L. Pouchet
248
10
0
22 Sep 2021
Is a Single Model Enough? MuCoS: A Multi-Model Ensemble Learning for
  Semantic Code Search
Is a Single Model Enough? MuCoS: A Multi-Model Ensemble Learning for Semantic Code Search
Lun Du
Xiaozhou Shi
Yanlin Wang
Ensheng Shi
Shi Han
Dongmei Zhang
267
4
0
10 Jul 2021
Memorization and Generalization in Neural Code Intelligence Models
Memorization and Generalization in Neural Code Intelligence Models
Md Rafiqul Islam Rabin
Aftab Hussain
Mohammad Amin Alipour
Vincent J. Hellendoorn
TDI
246
48
0
16 Jun 2021
Understanding Neural Code Intelligence Through Program Simplification
Understanding Neural Code Intelligence Through Program Simplification
Md Rafiqul Islam Rabin
Vincent J. Hellendoorn
Mohammad Amin Alipour
AAML
269
69
0
07 Jun 2021
WheaCha: A Method for Explaining the Predictions of Models of Code
WheaCha: A Method for Explaining the Predictions of Models of Code
Yu Wang
Ke Wang
Linzhang Wang
FAtt
215
5
0
09 Feb 2021
Generating Natural Adversarial Examples
Generating Natural Adversarial Examples
Zhengli Zhao
Dheeru Dua
Sameer Singh
GANAAML
567
641
0
31 Oct 2017
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