5 papers
Assigning Distinct Roles to Quantized and Low-Rank Matrices Toward Optimal Weight Decomposition
Yoonjun Cho, Soeun Kim, Dongjae Jeon +3
Decomposing weight matrices into quantization and low-rank components () is a widely used technique for compressing large lang…
R-TOFU: Unlearning in Large Reasoning Models
Sangyeon Yoon, Wonje Jeung, Albert No
Large Reasoning Models (LRMs) embed private or copyrighted information not only in their final answers but also throughout multi-step chain-of-thought (CoT) traces, making reliable…
SEPS: A Separability Measure for Robust Unlearning in LLMs
Wonje Jeung, Sangyeon Yoon, Albert No
Machine unlearning aims to selectively remove targeted knowledge from Large Language Models (LLMs), ensuring they forget specified content while retaining essential information. Ex…
Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios
Sangyeon Yoon, Wonje Jeung, Albert No
Auditing Differentially Private Stochastic Gradient Descent (DP-SGD) in the final model setting is challenging and often results in empirical lower bounds that are significantly lo…
Fully Quantized Always-on Face Detector Considering Mobile Image Sensors
Haechang Lee, Wongi Jeong, Dongil Ryu +4
Despite significant research on lightweight deep neural networks (DNNs) designed for edge devices, the current face detectors do not fully meet the requirements for "intelligent" C…