On the Use of ArXiv as a Dataset. - Colin B. Clement; Matthew Bierbaum; Kevin P. O'Keeffe; Alexander A. Alemi (CoRR, 2019)

PyMT5: multi-mode translation of natural language and Python code with transformers. - Colin B. Clement; Dawn Drain; Jonathan Timcheck; Alexey Svyatkovskiy; Neel Sundaresan (EMNLP (1), 2020)

Long-Range Modeling of Source Code Files with eWASH: Extended Window Access by Syntax Hierarchy. - Colin B. Clement; Shuai Lu; Xiaoyu Liu; Michele Tufano; Dawn Drain; Nan Duan; Neel Sundaresan; Alexey Svyatkovskiy (EMNLP (1), 2021)

GraphCodeBERT: Pre-training Code Representations with Data Flow. - Daya Guo; Shuo Ren; Shuai Lu; Zhangyin Feng; Duyu Tang; Shujie Liu 001; Long Zhou; Nan Duan; Alexey Svyatkovskiy; Shengyu Fu; Michele Tufano; Shao Kun Deng; et al. (ICLR, 2021)

CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation. - Shuai Lu; Daya Guo; Shuo Ren; Junjie Huang 008; Alexey Svyatkovskiy; Ambrosio Blanco; Colin B. Clement; Dawn Drain; Daxin Jiang; Duyu Tang; Ge Li 001; Lidong Zhou; et al. (NeurIPS Datasets and Benchmarks, 2021)

DeepDebug: Fixing Python Bugs Using Stack Traces, Backtranslation, and Code Skeletons. - Dawn Drain; Colin B. Clement; Guillermo Serrato; Neel Sundaresan (CoRR, 2021)

Distilling Transformers for Neural Cross-Domain Search. - Colin B. Clement; Chen Wu; Dawn Drain; Neel Sundaresan (CoRR, 2021)

Learning to Reduce False Positives in Analytic Bug Detectors. - Anant Kharkar; Roshanak Zilouchian Moghaddam; Matthew Jin; Xiaoyu Liu; Xin Shi; Colin B. Clement; Neel Sundaresan (ICSE, 2022)

Generating Examples from CLI Usage: Can Transformers Help? - Roshanak Zilouchian Moghaddam; Spandan Garg; Colin B. Clement; Yevhen Mohylevskyy; Neel Sundaresan (KDD, 2022)

DeepDev-PERF: a deep learning-based approach for improving software performance. - Spandan Garg; Roshanak Zilouchian Moghaddam; Colin B. Clement; Neel Sundaresan; Chen Wu (ESEC/SIGSOFT FSE, 2022)

Exploring and evaluating personalized models for code generation. - Andrei Zlotchevski; Dawn Drain; Alexey Svyatkovskiy; Colin B. Clement; Neel Sundaresan; Michele Tufano (ESEC/SIGSOFT FSE, 2022)

Training and Evaluating a Jupyter Notebook Data Science Assistant. - Shubham Chandel; Colin B. Clement; Guillermo Serrato; Neel Sundaresan (CoRR, 2022)

DeepPERF: A Deep Learning-Based Approach For Improving Software Performance. - Spandan Garg; Roshanak Zilouchian Moghaddam; Colin B. Clement; Neel Sundaresan; Chen Wu (CoRR, 2022)

Execution-based Evaluation for Data Science Code Generation Models. - Junjie Huang 008; Chenglong Wang; Jipeng Zhang; Cong Yan; Haotian Cui; Jeevana Priya Inala; Colin B. Clement; Nan Duan; Jianfeng Gao 001 (CoRR, 2022)

Program Translation via Code Distillation. - Yufan Huang; Mengnan Qi; Yongqiang Yao; Maoquan Wang; Bin Gu 001; Colin B. Clement; Neel Sundaresan (EMNLP, 2023)

SUT: Active Defects Probing for Transcompiler Models. - Mengnan Qi; Yufan Huang; Maoquan Wang; Yongqiang Yao; Zihan Liu; Bin Gu 001; Colin B. Clement; Neel Sundaresan (EMNLP, 2023)

Predicting Code Coverage without Execution. - Michele Tufano; Shubham Chandel; Anisha Agarwal; Neel Sundaresan; Colin B. Clement (CoRR, 2023)