3 citations · 7 across the 7 of their papers we have counts for
4 papers · 1 filter
Prompting and Fine-tuning Large Language Models for Automated Code Review Comment Generation
Md. Asif Haider, Ayesha Binte Mostofa, Sk. Sabit Bin Mosaddek +2
Generating accurate code review comments remains a significant challenge due to the inherently diverse and non-unique nature of the task output. Large language models pretrained on…
Can LLMs Replace Manual Annotation of Software Engineering Artifacts?
Toufique Ahmed, Premkumar Devanbu, Christoph Treude +1
Experimental evaluations of software engineering innovations, e.g., tools and processes, often include human-subject studies as a component of a multi-pronged strategy to obtain gr…
Trojans in Large Language Models of Code: A Critical Review through a Trigger-Based Taxonomy
Aftab Hussain, Md Rafiqul Islam Rabin, Toufique Ahmed +3
Large language models (LLMs) have provided a lot of exciting new capabilities in software development. However, the opaque nature of these models makes them difficult to reason abo…
Calibration and Correctness of Language Models for Code
Claudio Spiess, David Gros, Kunal Suresh Pai +6
Machine learning models are widely used, but can also often be wrong. Users would benefit from a reliable indication of whether a given output from a given model should be trusted,…