Unveiling Code Pre-Trained Models: Investigating Syntax and Semantics
Capacities

Unveiling Code Pre-Trained Models: Investigating Syntax and Semantics Capacities

20 December 2022

Yang Liu

Papers citing "Unveiling Code Pre-Trained Models: Investigating Syntax and Semantics Capacities"

5 / 5 papers shown

Title
Can Large Language Models Understand Intermediate Representations? Hailong Jiang Jianfeng Zhu Yao Wan B. Fang Hongyu Zhang Ruoming Jin Qiang Guan 48 1 0 07 Feb 2025
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 Shuai Lu Daya Guo Shuo Ren Junjie Huang Alexey Svyatkovskiy ... Nan Duan Neel Sundaresan Shao Kun Deng Shengyu Fu Shujie Liu ELM 188 853 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 220 3,054 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