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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"

4 / 4 papers shown
Title
LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs
LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs
Do Xuan Long
Hai Nguyen Ngoc
Tiviatis Sim
Hieu Dao
Shafiq R. Joty
Kenji Kawaguchi
Nancy F. Chen
Min-Yen Kan
34
7
0
16 Aug 2024
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
235
1,489
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
49
136
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
198
1,105
0
09 Feb 2021
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