192 citations · 845 across the 41 of their papers we have counts for
50 papers
Explaining Competitive-Level Programming Solutions using LLMs
Jierui Li, Szymon Tworkowski, Yingying Wu +1
In this paper, we approach competitive-level programming problem-solving as a composite task of reasoning and code generation. We propose a novel method to automatically annotate n…
Text-to-SQL Error Correction with Language Models of Code
Ziru Chen, Shijie Chen, Michael White +5
Despite recent progress in text-to-SQL parsing, current semantic parsers are still not accurate enough for practical use. In this paper, we investigate how to build automatic text-…
Learning Deep Semantics for Test Completion
Pengyu Nie, Rahul Banerjee, Junyi Jessy Li +2
Writing tests is a time-consuming yet essential task during software development. We propose to leverage recent advances in deep learning for text and code generation to assist dev…
Language-guided Task Adaptation for Imitation Learning
Prasoon Goyal, Raymond J. Mooney, Scott Niekum
We introduce a novel setting, wherein an agent needs to learn a task from a demonstration of a related task with the difference between the tasks communicated in natural language.…
Using Developer Discussions to Guide Fixing Bugs in Software
Sheena Panthaplackel, Milos Gligoric, Junyi Jessy Li +1
Automatically fixing software bugs is a challenging task. While recent work showed that natural language context is useful in guiding bug-fixing models, the approach required promp…
Zero-shot Video Moment Retrieval With Off-the-Shelf Models
Anuj Diwan, Puyuan Peng, Raymond J. Mooney
For the majority of the machine learning community, the expensive nature of collecting high-quality human-annotated data and the inability to efficiently finetune very large state-…