4 papers
Randomized Masked Finetuning: An Efficient Way to Mitigate Memorization of PIIs in LLMs
Kunj Joshi, David A. Smith
The current literature on memorization in Natural Language Models, especially Large Language Models (LLMs), poses severe security and privacy risks, as models tend to memorize pers…
Pre-Editorial Normalization for Automatically Transcribed Medieval Manuscripts in Old French and Latin
Thibault Clérice, Rachel Bawden, Anthony Glaise +2
Recent advances in Automatic Text Recognition (ATR) have improved access to historical archives, yet a methodological divide persists between palaeographic transcriptions and norma…
Post-Norm can Resharpen Attention
Pál Zsámboki, Benjamin Levi, David Ansel Josef Smith +4
Length Generalization is the essential capacity of autonomous agents to perform tasks in longer contexts than those encountered during training. To systematically study this feat,…
Multiple References with Meaningful Variations Improve Literary Machine Translation
Si Wu, John Wieting, David A. Smith
While a source sentence can be translated in many ways, most machine translation (MT) models are trained with only a single reference. Previous work has shown that using synthetic…