6 papers · 1 filter
Differentially-Private Text Rewriting reshapes Linguistic Style
Stefan Arnold
Differential Privacy (DP) for text matured from disjointed word-level substitutions to contiguous sentence-level rewriting by leveraging the generative capacity of language models.…
Steering Prepositional Phrases in Language Models: A Case of with-headed Adjectival and Adverbial Complements in Gemma-2
Stefan Arnold, René Gröbner
Language Models, when generating prepositional phrases, must often decide for whether their complements functions as an instrumental adjunct (describing the verb adverbially) or an…
Memorization in Language Models through the Lens of Intrinsic Dimension
Stefan Arnold
Language Models (LMs) are prone to memorizing parts of their data during training and unintentionally emitting them at generation time, raising concerns about privacy leakage and d…
Inspecting the Representation Manifold of Differentially-Private Text
Stefan Arnold
Differential Privacy (DP) for text has recently taken the form of text paraphrasing using language models and temperature sampling to better balance privacy and utility. However, t…
Characterizing Stereotypical Bias from Privacy-preserving Pre-Training
Stefan Arnold, Rene Gröbner, Annika Schreiner
Differential Privacy (DP) can be applied to raw text by exploiting the spatial arrangement of words in an embedding space. We investigate the implications of such text privatizatio…
Disentangling the Linguistic Competence of Privacy-Preserving BERT
Stefan Arnold, Nils Kemmerzell, Annika Schreiner
Differential Privacy (DP) has been tailored to address the unique challenges of text-to-text privatization. However, text-to-text privatization is known for degrading the performan…