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2020 – today
- 2024
[j2]Xiangru Tang, Andrew Tran, Jeffrey Tan, Mark B. Gerstein:
MolLM: a unified language model for integrating biomedical text with 2D and 3D molecular representations. Bioinform. 40(Supplement_1): i357-i368 (2024)- [c17]Stephen MacNeil
, Paul Denny, Andrew Tran, Juho Leinonen, Seth Bernstein, Arto Hellas, Sami Sarsa, Joanne Kim:
Decoding Logic Errors: A Comparative Study on Bug Detection by Students and Large Language Models. ACE 2024: 11-18 - [c16]Andrew Tran, Zixiu Guo, Carmen Leong, Giuseppe Daniele Ibello:
Moderating Technostress for Enhanced Student Learning Experiences: A Stress-is-Enhancing Mindset Approach. ICIS 2024 - 2023
- [c15]Xiangru Tang, Andrew Tran, Jeffrey Tan, Mark Gerstein:
GersteinLab at MEDIQA-Chat 2023: Clinical Note Summarization from Doctor-Patient Conversations through Fine-tuning and In-context Learning. ClinicalNLP@ACL 2023: 546-554 - [c14]Andrew Tran, Kenneth Angelikas, Egi Rama, Chiku Okechukwu, David H. Smith IV, Stephen MacNeil:
Generating Multiple Choice Questions for Computing Courses Using Large Language Models. FIE 2023: 1-8 - [c13]Andrew Tran, Linxuan Li, Egi Rama, Kenneth Angelikas, Stephen MacNeil:
Using Large Language Models to Automatically Identify Programming Concepts in Code Snippets. ICER (2) 2023: 22-23 - [c12]Juho Leinonen, Paul Denny, Stephen MacNeil, Sami Sarsa, Seth Bernstein, Joanne Kim, Andrew Tran, Arto Hellas:
Comparing Code Explanations Created by Students and Large Language Models. ITiCSE (1) 2023: 124-130 - [c11]Stephen MacNeil, Andrew Tran, Arto Hellas, Joanne Kim, Sami Sarsa, Paul Denny, Seth Bernstein, Juho Leinonen:
Experiences from Using Code Explanations Generated by Large Language Models in a Web Software Development E-Book. SIGCSE (1) 2023: 931-937 - [c10]Stephen MacNeil, Andrew Tran, Juho Leinonen, Paul Denny, Joanne Kim, Arto Hellas, Seth Bernstein, Sami Sarsa:
Automatically Generating CS Learning Materials with Large Language Models. SIGCSE (2) 2023: 1176 - [c9]Stephen MacNeil, Joanne Kim, Juho Leinonen, Paul Denny, Seth Bernstein, Brett A. Becker, Michel Wermelinger, Arto Hellas, Andrew Tran, Sami Sarsa, James Prather, Viraj Kumar:
The Implications of Large Language Models for CS Teachers and Students. SIGCSE (2) 2023: 1255 - [i6]Juho Leinonen, Paul Denny, Stephen MacNeil, Sami Sarsa, Seth Bernstein, Joanne Kim, Andrew Tran, Arto Hellas:
Comparing Code Explanations Created by Students and Large Language Models. CoRR abs/2304.03938 (2023) - [i5]Xiangru Tang, Andrew Tran, Jeffrey Tan, Mark Gerstein:
GersteinLab at MEDIQA-Chat 2023: Clinical Note Summarization from Doctor-Patient Conversations through Fine-tuning and In-context Learning. CoRR abs/2305.05001 (2023) - [i4]Stephen MacNeil, Andrew Tran, Joanne Kim, Ziheng Huang, Seth Bernstein, Dan Mogil:
Prompt Middleware: Mapping Prompts for Large Language Models to UI Affordances. CoRR abs/2307.01142 (2023) - [i3]Stephen MacNeil, Paul Denny, Andrew Tran, Juho Leinonen, Seth Bernstein, Arto Hellas, Sami Sarsa, Joanne Kim:
Decoding Logic Errors: A Comparative Study on Bug Detection by Students and Large Language Models. CoRR abs/2311.16017 (2023) - 2022
- [c8]Stephen MacNeil, Andrew Tran, Dan Mogil, Seth Bernstein, Erin Ross, Ziheng Huang:
Generating Diverse Code Explanations using the GPT-3 Large Language Model. ICER (2) 2022: 37-39 - [i2]Stephen MacNeil, Andrew Tran, Arto Hellas, Joanne Kim, Sami Sarsa, Paul Denny, Seth Bernstein, Juho Leinonen:
Experiences from Using Code Explanations Generated by Large Language Models in a Web Software Development E-Book. CoRR abs/2211.02265 (2022) - [i1]Stephen MacNeil, Andrew Tran, Juho Leinonen, Paul Denny, Joanne Kim, Arto Hellas, Seth Bernstein, Sami Sarsa:
Automatically Generating CS Learning Materials with Large Language Models. CoRR abs/2212.05113 (2022) - 2020
- [j1]Steven Rich, Andrew Tran, Aaron Williams, Jason Holt, Jeffery Sauer, Taylor Oshan:
arcos and arcospy: R and Python packages for accessing the DEA ARCOS database from 2006 - 2014. J. Open Source Softw. 5(53): 2450 (2020) - [c7]Santiago Correa, Noman Bashir, Andrew Tran, David E. Irwin, Jay Taneja:
Extend: A Framework for Increasing Energy Access by Interconnecting Solar Home Systems. COMPASS 2020: 265-273
2010 – 2019
- 2019
- [c6]Andrew Tran, Yamini Dasu, Anna Baynes:
Visual Analytic Process to Familiarize the Average Person with Ways to Apply Machine Learning. Visualization and Data Analysis 2019 - 2016
- [c5]Ying Choon Wu, Jeffery Wang, Andrew Tran, Alex Schperberg, John Caldwell, Tzyy-Ping Jung, Po-Chih Kuo:
MoBI-Box: A next generation Mobile Brain-Body Imaging Platform. CogSIMA 2016: 93-96 - 2010
- [c4]Ping Chen, David Brown, Andrew Tran, Noble Ozoka, Rafael Ortiz:
Word sense distribution in a web corpus. IEEE ICCI 2010: 449-453 - [c3]Andrew Tran, Chris Bowes, David Brown, Ping Chen, Max Choly, Wei Ding:
TreeMatch: A Fully Unsupervised WSD System Using Dependency Knowledge on a Specific Domain. SemEval@ACL 2010: 396-401
2000 – 2009
- 2009
- [c2]Jon McLachlan, Andrew Tran, Nicholas Hopper, Yongdae Kim:
Scalable onion routing with torsk. CCS 2009: 590-599 - [c1]Andrew Tran, Nicholas Hopper, Yongdae Kim:
Hashing it out in public: common failure modes of DHT-based anonymity schemes. WPES 2009: 71-80
Coauthor Index
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