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The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder
  Models for More Efficient Code Classification

The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code Classification

8 May 2023
Anastasiia Grishina
Max Hort
Leon Moonen
ArXivPDFHTML

Papers citing "The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code Classification"

4 / 4 papers shown
Title
A Critical Study of What Code-LLMs (Do Not) Learn
A Critical Study of What Code-LLMs (Do Not) Learn
Abhinav Anand
Shweta Verma
Krishna Narasimhan
Mira Mezini
35
4
0
17 Jun 2024
Deep Learning Meets Software Engineering: A Survey on Pre-Trained Models
  of Source Code
Deep Learning Meets Software Engineering: A Survey on Pre-Trained Models of Source Code
Changan Niu
Chuanyi Li
Bin Luo
Vincent Ng
SyDa
VLM
39
48
0
24 May 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
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
1