6 papers
Hey Pentti, We Did (More of) It!: A Vector-Symbolic Lisp With Residue Arithmetic
Connor Hanley, Eilene Tomkins-Flanaganm, Mary Alexandria Kelly
Using Frequency-domain Holographic Reduced Representations (FHRRs), we extend a Vector-Symbolic Architecture (VSA) encoding of Lisp 1.5 with primitives for arithmetic operations us…
Hey Pentti, We Did It!: A Fully Vector-Symbolic Lisp
Eilene Tomkins-Flanagan, Mary A. Kelly
Kanerva (2014) suggested that it would be possible to construct a complete Lisp out of a vector-symbolic architecture. We present the general form of a vector-symbolic representati…
Hey Pentti, We Did It Again!: Differentiable vector-symbolic types that prove polynomial termination
Eilene Tomkins-Flanagan, Connor Hanley, Mary A. Kelly
We present a typed computer language, Doug, in which all typed programs may be proved to halt in polynomial time, encoded in a vector-symbolic architecture (VSA). Doug is just an e…
Bridging Generative Networks with the Common Model of Cognition
Robert L. West, Spencer Eckler, Brendan Conway-Smith +3
This article presents a theoretical framework for adapting the Common Model of Cognition to large generative network models within the field of artificial intelligence. This can be…
A Neuro-mimetic Realization of the Common Model of Cognition via Hebbian Learning and Free Energy Minimization
Alexander Ororbia, Mary Alexandria Kelly
Over the last few years, large neural generative models, capable of synthesizing semantically rich passages of text or producing complex images, have recently emerged as a popular…
Like a bilingual baby: The advantage of visually grounding a bilingual language model
Khai-Nguyen Nguyen, Zixin Tang, Ankur Mali +1
Unlike most neural language models, humans learn language in a rich, multi-sensory and, often, multi-lingual environment. Current language models typically fail to fully capture th…