INSPECT: Intrinsic and Systematic Probing Evaluation for Code Transformers

8 December 2023

Papers citing "INSPECT: Intrinsic and Systematic Probing Evaluation for Code Transformers"

7 / 7 papers shown

Title
A Survey on Adversarial Machine Learning for Code Data: Realistic Threats, Countermeasures, and Interpretations Yulong Yang Haoran Fan Chenhao Lin Qian Li Zhengyu Zhao Chao Shen Xiaohong Guan AAML 38 0 0 12 Nov 2024
An Empirical Study on Capability of Large Language Models in Understanding Code Semantics Thu-Trang Nguyen Thanh Trong Vu H. Vo Son Nguyen ELM 33 2 0 04 Jul 2024
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation Yue Wang Weishi Wang Shafiq R. Joty S. Hoi 210 1,451 0 02 Sep 2021
Probing Classifiers: Promises, Shortcomings, and Advances Yonatan Belinkov 221 402 0 24 Feb 2021
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
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 226 4,424 0 23 Jan 2020
What you can cram into a single vector: Probing sentence embeddings for linguistic properties Alexis Conneau Germán Kruszewski Guillaume Lample Loïc Barrault Marco Baroni 199 876 0 03 May 2018