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cs.LG2026
Understanding Private Evolution as Learning-Augmented Clustering
Audra McMillan, Kunal Talwar, Felix Zhou
Private Evolution (PE) is a differentially private algorithm for synthetic data generation. While it can be viewed as a Wasserstein learning algorithm, it performs much better in p…
cs.CL2026
Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts
Jiayuan Ye, Vitaly Feldman, Kunal Talwar
Large language models (LLMs) can struggle to memorize factual knowledge in their parameters, often leading to hallucinations and poor performance on knowledge-intensive tasks. In t…