2 citations · 2 across the 1 of their papers we have counts for
3 papers
cs.SE2026★ 2 cited
Clotho: Measuring Task-Specific Pre-Generation Test Adequacy for LLM Inputs
Juyeon Yoon, Somin Kim, Robert Feldt +1
Software increasingly relies on the emergent capabilities of Large Language Models (LLMs), from natural language understanding to program analysis and generation. Yet testing them…
cs.SE2025
Capturing Semantic Flow of ML-based Systems
Shin Yoo, Robert Feldt, Somin Kim +1
ML-based systems are software systems that incorporates machine learning components such as Deep Neural Networks (DNNs) or Large Language Models (LLMs). While such systems enable a…
cs.SE2025
DANDI: Diffusion as Normative Distribution for Deep Neural Network Input
Somin Kim, Shin Yoo
Surprise Adequacy (SA) has been widely studied as a test adequacy metric that can effectively guide software engineers towards inputs that are more likely to reveal unexpected beha…