23 citations · 74 across the 6 of their papers we have counts for
6 papers
Fundamental Principles of Linguistic Structure are Not Represented by o3
Elliot Murphy, Evelina Leivada, Vittoria Dentella +2
A core component of a successful artificial general intelligence would be the rapid creation and manipulation of grounded compositional abstractions and the demonstration of expert…
A Sentence is Worth a Thousand Pictures: Can Large Language Models Understand Hum4n L4ngu4ge and the W0rld behind W0rds?
Evelina Leivada, Gary Marcus, Fritz Günther +1
Modern Artificial Intelligence applications show great potential for language-related tasks that rely on next-word prediction. The current generation of Large Language Models (LLMs…
Getting from Generative AI to Trustworthy AI: What LLMs might learn from Cyc
Doug Lenat, Gary Marcus
Generative AI, the most popular current approach to AI, consists of large language models (LLMs) that are trained to produce outputs that are plausible, but not necessarily correct…
Testing AI on language comprehension tasks reveals insensitivity to underlying meaning
Vittoria Dentella, Fritz Guenther, Elliot Murphy +2
Large Language Models (LLMs) are recruited in applications that span from clinical assistance and legal support to question answering and education. Their success in specialized ta…
DALL-E 2 Fails to Reliably Capture Common Syntactic Processes
Evelina Leivada, Elliot Murphy, Gary Marcus
Machine intelligence is increasingly being linked to claims about sentience, language processing, and an ability to comprehend and transform natural language into a range of stimul…
Solutions to problems with deep learning
J Gerard Wolff
Despite the several successes of deep learning systems, there are concerns about their limitations, discussed most recently by Gary Marcus. This paper discusses Marcus's concerns a…