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Toward a Theory of Causation for Interpreting Neural Code Models

Toward a Theory of Causation for Interpreting Neural Code Models

7 February 2023
David Nader-Palacio
Alejandro Velasco
Nathan Cooper
Á. Rodríguez
Kevin Moran
Denys Poshyvanyk
ArXivPDFHTML

Papers citing "Toward a Theory of Causation for Interpreting Neural Code Models"

3 / 3 papers shown
Title
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
196
853
0
09 Feb 2021
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Jinpeng Wang
Amanpreet Singh
Julian Michael
Felix Hill
Omer Levy
Samuel R. Bowman
ELM
297
6,950
0
20 Apr 2018
Towards A Rigorous Science of Interpretable Machine Learning
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
227
3,681
0
28 Feb 2017
1