9 citations · 9 across the 4 of their papers we have counts for
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cs.SE2024
The Counterfeit Conundrum: Can Code Language Models Grasp the Nuances of Their Incorrect Generations?
Alex Gu, Wen-Ding Li, Naman Jain +4
While language models are increasingly more proficient at code generation, they still frequently generate incorrect programs. Many of these programs are obviously wrong, but others…
cs.SE2022
MP-CodeCheck: Evolving Logical Expression Code Anomaly Learning with Iterative Self-Supervision
Urs C. Muff, Celine Lee, Paul Gottschlich +1
Machine programming (MP) is concerned with automating software development. According to studies, software engineers spend upwards of 50% of their development time debugging softwa…
cs.SE2021★ 9 cited
Toward Code Generation: A Survey and Lessons from Semantic Parsing
Celine Lee, Justin Gottschlich, Dan Roth
With the growth of natural language processing techniques and demand for improved software engineering efficiency, there is an emerging interest in translating intention from human…