activity
20222025
most citedComparing Code Explanations Created by Students and Large Language Models

195 citations · 256 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2025★ 4 cited

TreeMatch: A Fully Unsupervised WSD System Using Dependency Knowledge on a Specific Domain

Andrew Tran, Chris Bowes, David Brown +3

Word sense disambiguation (WSD) is one of the main challenges in Computational Linguistics. TreeMatch is a WSD system originally developed using data from SemEval 2007 Task 7 (Coar…

cs.HC2023★ 1 cited

Decoding Logic Errors: A Comparative Study on Bug Detection by Students and Large Language Models

Stephen MacNeil, Paul Denny, Andrew Tran +5

Identifying and resolving logic errors can be one of the most frustrating challenges for novices programmers. Unlike syntax errors, for which a compiler or interpreter can issue a…

cs.HC2023★ 8 cited

Prompt Middleware: Mapping Prompts for Large Language Models to UI Affordances

Stephen MacNeil, Andrew Tran, Joanne Kim +3

To help users do complex work, researchers have developed techniques to integrate AI and human intelligence into user interfaces (UIs). With the recent introduction of large langua…

cs.CL2023★ 2 cited

GersteinLab at MEDIQA-Chat 2023: Clinical Note Summarization from Doctor-Patient Conversations through Fine-tuning and In-context Learning

Xiangru Tang, Andrew Tran, Jeffrey Tan +1

This paper presents our contribution to the MEDIQA-2023 Dialogue2Note shared task, encompassing both subtask A and subtask B. We approach the task as a dialogue summarization probl…

cs.CY2023★ 195 cited

Comparing Code Explanations Created by Students and Large Language Models

Juho Leinonen, Paul Denny, Stephen MacNeil +5

Reasoning about code and explaining its purpose are fundamental skills for computer scientists. There has been extensive research in the field of computing education on the relatio…

cs.CY2022★ 43 cited

Automatically Generating CS Learning Materials with Large Language Models

Stephen MacNeil, Andrew Tran, Juho Leinonen +5

Recent breakthroughs in Large Language Models (LLMs), such as GPT-3 and Codex, now enable software developers to generate code based on a natural language prompt. Within computer s…

cs.SE2022★ 3 cited

Experiences from Using Code Explanations Generated by Large Language Models in a Web Software Development E-Book

Stephen MacNeil, Andrew Tran, Arto Hellas +5

Advances in natural language processing have resulted in large language models (LLMs) that are capable of generating understandable and sensible written text. Recent versions of th…