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ORCIDCollin McMillan
- > Home > Persons > Collin McMillan
Publications
- 2024
[j17]Yifan Zhang
, Jiliang Li, Zachary Karas, Aakash Bansal, Toby Jia-Jun Li, Collin McMillan, Kevin Leach, Yu Huang:
EyeTrans: Merging Human and Machine Attention for Neural Code Summarization. Proc. ACM Softw. Eng. 1(FSE): 115-136 (2024)- [c62]Ningzhi Tang, Junwen An, Meng Chen, Aakash Bansal, Yu Huang, Collin McMillan, Toby Jia-Jun Li:
CodeGRITS: A Research Toolkit for Developer Behavior and Eye Tracking in IDE. ICSE Companion 2024: 119-123 - [i33]Yifan Zhang, Jiliang Li, Zachary Karas, Aakash Bansal, Toby Jia-Jun Li, Collin McMillan, Kevin Leach, Yu Huang:
EyeTrans: Merging Human and Machine Attention for Neural Code Summarization. CoRR abs/2402.14096 (2024) - [i31]Ningzhi Tang, Meng Chen, Zheng Ning, Aakash Bansal, Yu Huang, Collin McMillan, Toby Jia-Jun Li:
A Study on Developer Behaviors for Validating and Repairing LLM-Generated Code Using Eye Tracking and IDE Actions. CoRR abs/2405.16081 (2024) - [i30]Aakash Bansal, Robert Wallace, Zachary Karas, Ningzhi Tang, Yu Huang, Toby Jia-Jun Li, Collin McMillan:
Programmer Visual Attention During Context-Aware Code Summarization. CoRR abs/2405.18573 (2024) - 2023
- [j16]Aakash Bansal, Bonita Sharif, Collin McMillan:
Towards Modeling Human Attention from Eye Movements for Neural Source Code Summarization. Proc. ACM Hum. Comput. Interact. 7(ETRA): 1-19 (2023) - [j15]Aakash Bansal, Zachary Eberhart, Zachary Karas, Yu Huang, Collin McMillan:
Function Call Graph Context Encoding for Neural Source Code Summarization. IEEE Trans. Software Eng. 49(9): 4268-4281 (2023) - [c59]Sakib Haque, Aakash Bansal, Collin McMillan:
Label Smoothing Improves Neural Source Code Summarization. ICPC 2023: 101-112 - [c58]Aakash Bansal, Chia-Yi Su, Zachary Karas, Yifan Zhang, Yu Huang, Toby Jia-Jun Li, Collin McMillan:
Modeling Programmer Attention as Scanpath Prediction. ASE 2023: 1732-1736 - [c57]Chia-Yi Su, Aakash Bansal, Vijayanta Jain, Sepideh Ghanavati, Collin McMillan:
A Language Model of Java Methods with Train/Test Deduplication. ESEC/SIGSOFT FSE 2023: 2152-2156 - [i29]Sakib Haque, Aakash Bansal, Collin McMillan:
Label Smoothing Improves Neural Source Code Summarization. CoRR abs/2303.16178 (2023) - [i28]Chia-Yi Su, Aakash Bansal, Vijayanta Jain, Sepideh Ghanavati, Collin McMillan:
A Language Model of Java Methods with Train/Test Deduplication. CoRR abs/2305.08286 (2023) - [i27]Aakash Bansal, Bonita Sharif, Collin McMillan:
Towards Modeling Human Attention from Eye Movements for Neural Source Code Summarization. CoRR abs/2305.09773 (2023) - [i25]Aakash Bansal, Siyuan Jiang, Sakib Haque, Collin McMillan:
Statement-based Memory for Neural Source Code Summarization. CoRR abs/2307.11709 (2023) - [i23]Aakash Bansal, Chia-Yi Su, Zachary Karas, Yifan Zhang, Yu Huang, Toby Jia-Jun Li, Collin McMillan:
Modeling Programmer Attention as Scanpath Prediction. CoRR abs/2308.13920 (2023) - [i21]Aakash Bansal, Chia-Yi Su, Collin McMillan:
Revisiting File Context for Source Code Summarization. CoRR abs/2309.02326 (2023) - 2022
- [j14]Zachary Eberhart, Aakash Bansal, Collin McMillan:
A Wizard of Oz Study Simulating API Usage Dialogues With a Virtual Assistant. IEEE Trans. Software Eng. 48(6): 1883-1904 (2022) - [c56]Sakib Haque, Zachary Eberhart, Aakash Bansal, Collin McMillan:
Semantic similarity metrics for evaluating source code summarization. ICPC 2022: 36-47 - [i19]Sakib Haque, Zachary Eberhart, Aakash Bansal, Collin McMillan:
Semantic Similarity Metrics for Evaluating Source Code Summarization. CoRR abs/2204.01632 (2022) - 2021
- [c52]Alexander LeClair, Aakash Bansal, Collin McMillan:
Ensemble Models for Neural Source Code Summarization of Subroutines. ICSME 2021: 286-297 - [c51]Aakash Bansal, Sakib Haque, Collin McMillan:
Project-Level Encoding for Neural Source Code Summarization of Subroutines. ICPC 2021: 253-264 - [c50]Aakash Bansal, Zachary Eberhart, Lingfei Wu, Collin McMillan:
A Neural Question Answering System for Basic Questions about Subroutines. SANER 2021: 60-71 - [c49]Sakib Haque, Aakash Bansal, Lingfei Wu, Collin McMillan:
Action Word Prediction for Neural Source Code Summarization. SANER 2021: 330-341 - [i18]Sakib Haque, Aakash Bansal, Lingfei Wu, Collin McMillan:
Action Word Prediction for Neural Source Code Summarization. CoRR abs/2101.02742 (2021) - [i17]Aakash Bansal, Zachary Eberhart, Lingfei Wu, Collin McMillan:
A Neural Question Answering System for Basic Questions about Subroutines. CoRR abs/2101.03999 (2021) - [i16]Aakash Bansal, Sakib Haque, Collin McMillan:
Project-Level Encoding for Neural Source Code Summarization of Subroutines. CoRR abs/2103.11599 (2021) - [i15]Zachary Eberhart, Aakash Bansal, Collin McMillan:
A Wizard of Oz Study Simulating API Usage Dialogues with a Virtual Assistant. CoRR abs/2106.12645 (2021) - [i14]Alexander LeClair, Aakash Bansal, Collin McMillan:
Ensemble Models for Neural Source Code Summarization of Subroutines. CoRR abs/2107.11423 (2021) - 2020
- [i12]Zachary Eberhart, Aakash Bansal, Collin McMillan:
The Apiza Corpus: API Usage Dialogues with a Simulated Virtual Assistant. CoRR abs/2001.09925 (2020)
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last updated on 2024-08-05 20:23 CEST by the dblp team
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