2 citations · 2 across the 4 of their papers we have counts for
7 papers
Co-occurring associated retained concepts in Diffusion Unlearning
Miso Kim, Georu Lee, Yunji Kim +3
Unlearning has emerged as a key technique to mitigate harmful content generation in diffusion models. However, existing methods often remove not only the target concept, but also b…
Stability Analysis of Sharpness-Aware Minimization
Hoki Kim, Jinseong Park, Yujin Choi +1
Sharpness-aware minimization (SAM) is a training method that seeks to find flat minima in deep learning, resulting in state-of-the-art performance across various domains. Instead o…
Machine Unlearning for Masked Diffusion Language Models
Georu Lee, Seungwon Jeong, Hoki Kim +2
Recent masked diffusion language models (MDLMs), such as LLaDA and Dream, have achieved performance comparable to autoregressive large language models. Unlike autoregressive models…
CyBiasBench: Benchmarking Bias in LLM Agents for Cyber-Attack Scenarios
Taein Lim, Seongyong Ju, Munhyeok Kim +2
Large language models (LLMs) are increasingly deployed as autonomous agents in offensive cybersecurity. In this paper, we reveal an interesting phenomenon: different agents exhibit…
CaddieSet: A Golf Swing Dataset with Human Joint Features and Ball Information
Seunghyeon Jung, Seoyoung Hong, Jiwoo Jeong +4
Recent advances in deep learning have led to more studies to enhance golfers' shot precision. However, these existing studies have not quantitatively established the relationship b…
Are Self-Attentions Effective for Time Series Forecasting?
Dongbin Kim, Jinseong Park, Jaewook Lee +1
Time series forecasting is crucial for applications across multiple domains and various scenarios. Although Transformer models have dramatically advanced the landscape of forecasti…