2 papers
cs.LG2026
Seq2Synth: Benchmarking Temporal Fidelity in Synthetic Sequential Tabular Data
Kiwan Kwon, Kangmin Kim, Hojin Lee +5
Synthetic sequential tabular data are increasingly used for privacy-preserving data sharing and data-driven research, but evaluating their fidelity remains difficult because tempor…
cs.LG2026
Unlearning's Blind Spots: Over-Unlearning and Prototypical Relearning Attack
SeungBum Ha, Saerom Park, Sung Whan Yoon
Machine unlearning (MU) aims to expunge a designated forget set from a trained model without costly retraining, yet the existing techniques overlook two critical blind spots: "over…