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Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in
  Code Models

Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in Code Models

2 October 2023
Zhou Yang
Zhipeng Zhao
Chenyu Wang
Jieke Shi
Dongsum Kim
Donggyun Han
David Lo
    SILM
    AAML
    MIACV
ArXivPDFHTML

Papers citing "Gotcha! This Model Uses My Code! Evaluating Membership Leakage Risks in Code Models"

4 / 4 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
201
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
Extracting Training Data from Large Language Models
Extracting Training Data from Large Language Models
Nicholas Carlini
Florian Tramèr
Eric Wallace
Matthew Jagielski
Ariel Herbert-Voss
...
Tom B. Brown
D. Song
Ulfar Erlingsson
Alina Oprea
Colin Raffel
MLAU
SILM
267
1,798
0
14 Dec 2020
Semantic Robustness of Models of Source Code
Semantic Robustness of Models of Source Code
Goutham Ramakrishnan
Jordan Henkel
Zi Wang
Aws Albarghouthi
S. Jha
Thomas W. Reps
SILM
AAML
35
95
0
07 Feb 2020
1