27 citations · 28 across the 3 of their papers we have counts for
3 papers
cs.SE2025
DeCon: Detecting Incorrect Assertions via Postconditions Generated by a Large Language Model
Hao Yu, Tianyu Chen, Jiaming Huang +8
Recently, given the docstring for the target problem and the target function signature, large language models (LLMs) have been used not only to generate source code, but also to ge…
cs.SE2024★ 1 cited
Log Parsing using LLMs with Self-Generated In-Context Learning and Self-Correction
Yifan Wu, Siyu Yu, Ying Li
Log parsing transforms log messages into structured formats, serving as a crucial step for log analysis. Despite a variety of log parsers that have been proposed, their performance…
cs.SE2023★ 27 cited
CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models
Hao Yu, Bo Shen, Dezhi Ran +7
Code generation models based on the pre-training and fine-tuning paradigm have been increasingly attempted by both academia and industry, resulting in well-known industrial models…