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Learning to Represent Edits

Learning to Represent Edits

31 October 2018
Pengcheng Yin
Graham Neubig
Miltiadis Allamanis
Marc Brockschmidt
Alexander L. Gaunt
    KELM
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Papers citing "Learning to Represent Edits"

21 / 21 papers shown
Title
Implant Global and Local Hierarchy Information to Sequence based Code
  Representation Models
Implant Global and Local Hierarchy Information to Sequence based Code Representation Models
Kechi Zhang
Zhuo Li
Zhi Jin
Ge Li
29
7
0
14 Mar 2023
KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program
  Repair
KNOD: Domain Knowledge Distilled Tree Decoder for Automated Program Repair
Nan Jiang
Thibaud Lutellier
Yiling Lou
Lin Tan
Dan Goldwasser
Xinming Zhang
27
43
0
03 Feb 2023
CoditT5: Pretraining for Source Code and Natural Language Editing
CoditT5: Pretraining for Source Code and Natural Language Editing
Jiyang Zhang
Sheena Panthaplackel
Pengyu Nie
Junyi Jessy Li
Miloš Gligorić
KELM
22
88
0
10 Aug 2022
Overwatch: Learning Patterns in Code Edit Sequences
Overwatch: Learning Patterns in Code Edit Sequences
Yuhao Zhang
Yasharth Bajpai
Priyanshu Gupta
Ameya Ketkar
Miltiadis Allamanis
...
Sumit Gulwani
Arjun Radhakrishna
Mohammad Raza
Gustavo Soares
A. Tiwari
11
13
0
25 Jul 2022
NewsEdits: A News Article Revision Dataset and a Document-Level
  Reasoning Challenge
NewsEdits: A News Article Revision Dataset and a Document-Level Reasoning Challenge
Alexander Spangher
Xiang Ren
Jonathan May
Nanyun Peng
KELM
30
22
0
14 Jun 2022
Learning to Model Editing Processes
Learning to Model Editing Processes
Machel Reid
Graham Neubig
KELM
BDL
116
35
0
24 May 2022
On Distribution Shift in Learning-based Bug Detectors
On Distribution Shift in Learning-based Bug Detectors
Jingxuan He
Luca Beurer-Kellner
Martin Vechev
24
18
0
21 Apr 2022
LAMNER: Code Comment Generation Using Character Language Model and Named
  Entity Recognition
LAMNER: Code Comment Generation Using Character Language Model and Named Entity Recognition
Rishab Sharma
Fuxiang Chen
Fatemeh H. Fard
42
2
0
05 Apr 2022
VarCLR: Variable Semantic Representation Pre-training via Contrastive
  Learning
VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning
Qibin Chen
Jeremy Lacomis
Edward J. Schwartz
Graham Neubig
Bogdan Vasilescu
Claire Le Goues
VLM
21
34
0
05 Dec 2021
Learning Structural Edits via Incremental Tree Transformations
Learning Structural Edits via Incremental Tree Transformations
Ziyu Yao
Frank F. Xu
Pengcheng Yin
Huan Sun
Graham Neubig
CLL
154
27
0
28 Jan 2021
Learning to Represent Programs with Heterogeneous Graphs
Learning to Represent Programs with Heterogeneous Graphs
Kechi Zhang
Wenhan Wang
Huangzhao Zhang
Ge Li
Zhi Jin
GNN
21
63
0
08 Dec 2020
Text Editing by Command
Text Editing by Command
Felix Faltings
Michel Galley
Gerold Hintz
Chris Brockett
Chris Quirk
Jianfeng Gao
Bill Dolan
KELM
147
37
0
24 Oct 2020
A Systematic Literature Review on the Use of Deep Learning in Software
  Engineering Research
A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research
Cody Watson
Nathan Cooper
David Nader-Palacio
Kevin Moran
Denys Poshyvanyk
26
111
0
14 Sep 2020
Fact-based Text Editing
Fact-based Text Editing
Hayate Iso
Chao Qiao
Hang Li
KELM
39
23
0
02 Jul 2020
Learning Sparse Prototypes for Text Generation
Learning Sparse Prototypes for Text Generation
Junxian He
Taylor Berg-Kirkpatrick
Graham Neubig
27
23
0
29 Jun 2020
Copy that! Editing Sequences by Copying Spans
Copy that! Editing Sequences by Copying Spans
Sheena Panthaplackel
Miltiadis Allamanis
Marc Brockschmidt
BDL
21
28
0
08 Jun 2020
A Structural Model for Contextual Code Changes
A Structural Model for Contextual Code Changes
Shaked Brody
Uri Alon
Eran Yahav
KELM
24
7
0
27 May 2020
Learning to Update Natural Language Comments Based on Code Changes
Learning to Update Natural Language Comments Based on Code Changes
Sheena Panthaplackel
Pengyu Nie
Miloš Gligorić
Junyi Jessy Li
Raymond J. Mooney
29
63
0
25 Apr 2020
ProGraML: Graph-based Deep Learning for Program Optimization and
  Analysis
ProGraML: Graph-based Deep Learning for Program Optimization and Analysis
Chris Cummins
Zacharias V. Fisches
Tal Ben-Nun
Torsten Hoefler
Hugh Leather
88
56
0
23 Mar 2020
A Literature Study of Embeddings on Source Code
A Literature Study of Embeddings on Source Code
Zimin Chen
Monperrus Martin
49
82
0
05 Apr 2019
Effective Approaches to Attention-based Neural Machine Translation
Effective Approaches to Attention-based Neural Machine Translation
Thang Luong
Hieu H. Pham
Christopher D. Manning
218
7,926
0
17 Aug 2015
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