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IntelliExplain: Enhancing Interactive Code Generation through Natural
  Language Explanations for Non-Professional Programmers

IntelliExplain: Enhancing Interactive Code Generation through Natural Language Explanations for Non-Professional Programmers

16 May 2024
Hao Yan
Thomas D. Latoza
Ziyu Yao
    LRM
ArXivPDFHTML

Papers citing "IntelliExplain: Enhancing Interactive Code Generation through Natural Language Explanations for Non-Professional Programmers"

4 / 4 papers shown
Title
Grounded Copilot: How Programmers Interact with Code-Generating Models
Grounded Copilot: How Programmers Interact with Code-Generating Models
Shraddha Barke
M. James
Nadia Polikarpova
136
212
0
30 Jun 2022
Large Language Models are Zero-Shot Reasoners
Large Language Models are Zero-Shot Reasoners
Takeshi Kojima
S. Gu
Machel Reid
Yutaka Matsuo
Yusuke Iwasawa
ReLM
LRM
291
2,712
0
24 May 2022
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
301
11,730
0
04 Mar 2022
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for
  Code Understanding and Generation
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation
Yue Wang
Weishi Wang
Shafiq R. Joty
S. Hoi
204
1,451
0
02 Sep 2021
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