5 citations · 9 across the 21 of their papers we have counts for
Showing cs.SEShow all
2 papers · 1 filter
cs.SE2025
How Diversely Can Language Models Solve Problems? Exploring the Algorithmic Diversity of Model-Generated Code
Seonghyeon Lee, Heejae Chon, Joonwon Jang +2
Language models (LMs) have exhibited impressive abilities in generating code from natural language requirements. In this work, we highlight the diversity of code generated by LMs a…
cs.SE2024
Eliciting Instruction-tuned Code Language Models' Capabilities to Utilize Auxiliary Function for Code Generation
Seonghyeon Lee, Suyeon Kim, Joonwon Jang +3
We study the code generation behavior of instruction-tuned models built on top of code pre-trained language models when they could access an auxiliary function to implement a funct…