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Exploring the Impact of the Output Format on the Evaluation of Large
  Language Models for Code Translation

Exploring the Impact of the Output Format on the Evaluation of Large Language Models for Code Translation

25 March 2024
Marcos Macedo
Yuan Tian
F. Côgo
Bram Adams
ArXivPDFHTML

Papers citing "Exploring the Impact of the Output Format on the Evaluation of Large Language Models for Code Translation"

3 / 3 papers shown
Title
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
DOBF: A Deobfuscation Pre-Training Objective for Programming Languages
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
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding
  and Generation
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
Shuai Lu
Daya Guo
Shuo Ren
Junjie Huang
Alexey Svyatkovskiy
...
Nan Duan
Neel Sundaresan
Shao Kun Deng
Shengyu Fu
Shujie Liu
ELM
190
853
0
09 Feb 2021
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