1.3k citations · 3.2k across the 29 of their papers we have counts for
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Language Model Inversion
John X. Morris, Wenting Zhao, Justin T. Chiu +2
Language models produce a distribution over the next token; can we use this information to recover the prompt tokens? We consider the problem of language model inversion and show t…
Text Embeddings Reveal (Almost) As Much As Text
John X. Morris, Volodymyr Kuleshov, Vitaly Shmatikov +1
How much private information do text embeddings reveal about the original text? We investigate the problem of embedding \textit{inversion}, reconstructing the full text represented…
Adversarial Semantic Collisions
Congzheng Song, Alexander M. Rush, Vitaly Shmatikov
We study semantic collisions: texts that are semantically unrelated but judged as similar by NLP models. We develop gradient-based approaches for generating semantic collisions and…
Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning
Roei Schuster, Tal Schuster, Yoav Meri +1
Word embeddings, i.e., low-dimensional vector representations such as GloVe and SGNS, encode word "meaning" in the sense that distances between words' vectors correspond to their s…