NLPerturbator: Studying the Robustness of Code LLMs to Natural Language Variations

28 June 2024

Papers citing "NLPerturbator: Studying the Robustness of Code LLMs to Natural Language Variations"

6 / 6 papers shown

Title
CODECRASH: Stress Testing LLM Reasoning under Structural and Semantic Perturbations Man Ho Adrian Lam Chaozheng Wang Jen-tse Huang M. Lyu LRM 29 0 0 19 Apr 2025
RobuNFR: Evaluating the Robustness of Large Language Models on Non-Functional Requirements Aware Code Generation Feng Lin Dong Jae Kim Z. Li Jinqiu Yang Tse-Husn Chen AAML 38 0 0 28 Mar 2025
Reasoning Runtime Behavior of a Program with LLM: How Far Are We? Junkai Chen Zhiyuan Pan Xing Hu Zhenhao Li Ge Li Xin Xia LRM 32 20 0 25 Mar 2024
CodeGen2: Lessons for Training LLMs on Programming and Natural Languages Erik Nijkamp A. Ghobadzadeh Caiming Xiong Silvio Savarese Yingbo Zhou 144 163 0 03 May 2023
CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning Hung Le Yue Wang Akhilesh Deepak Gotmare Silvio Savarese S. Hoi SyDa ALM 124 232 0 05 Jul 2022
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