18 citations · 71 across the 14 of their papers we have counts for
15 papers
Token embeddings violate the manifold hypothesis
Michael Robinson, Sourya Dey, Tony Chiang
A full understanding of the behavior of a large language model (LLM) requires our grasp of its input token space. If this space differs from our assumptions, our comprehension of a…
Probing the topology of the space of tokens with structured prompts
Michael Robinson, Sourya Dey, Taisa Kushner
This article presents a general and flexible method for prompting a large language model (LLM) to reveal its (hidden) token input embedding up to homeomorphism. Moreover, this arti…
The structure of the token space for large language models
Michael Robinson, Sourya Dey, Shauna Sweet
Large language models encode the correlational structure present in natural language by fitting segments of utterances (tokens) into a high dimensional ambient latent space upon wh…
A Simulated Reconstruction and Reidentification Attack on the 2010 U.S. Census
John M. Abowd, Tamara Adams, Robert Ashmead +12
We show that individual, confidential microdata records from the 2010 U.S. Census of Population and Housing can be accurately reconstructed from the published tabular summaries. Ni…
Dynamic Mode Decomposition and Koopman Theory
Sourya Dey
Dynamic Mode Decomposition (DMD) is a technique to approximate generally non-linear dynamical systems using linear techniques, which are better understood and easier to analyze. Ko…
DLKoopman: A deep learning software package for Koopman theory
Sourya Dey, Eric Davis
We present DLKoopman -- a software package for Koopman theory that uses deep learning to learn an encoding of a nonlinear dynamical system into a linear space, while simultaneously…