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19992026
most citedThe Symbol Grounding Problem

2.6k citations · 4k across the 31 of their papers we have counts for

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cs.CL2026

Tolerance Principle and Small Language Model Learning

Adam E. Friedman, Stevan Harnad, Rushen Shi

Modern language models like GPT-3, BERT, and LLaMA require massive training data, yet with sufficient training they reliably learn to distinguish grammatical from ungrammatical sen…

cs.CL2024★ 6 cited

Language Writ Large: LLMs, ChatGPT, Grounding, Meaning and Understanding

Stevan Harnad

Apart from what (little) OpenAI may be concealing from us, we all know (roughly) how ChatGPT works (its huge text database, its statistics, its vector representations, and their hu…

cs.CL2014

The Latent Structure of Dictionaries

Philippe Vincent-Lamarre, Alexandre Blondin Massé, Marcos Lopes +3

How many words (and which ones) are sufficient to define all other words? When dictionaries are analyzed as directed graphs with links from defining words to defined words, they re…

cs.CL2013★ 1 cited

Hidden Structure and Function in the Lexicon

Olivier Picard, Mélanie Lord, Alexandre Blondin-Massé +3

How many words are needed to define all the words in a dictionary? Graph-theoretic analysis reveals that about 10% of a dictionary is a unique Kernel of words that define one anoth…

cs.CL2009★ 10 cited

Hierarchies in Dictionary Definition Space

Olivier Picard, Alexandre Blondin-Masse, Stevan Harnad +3

A dictionary defines words in terms of other words. Definitions can tell you the meanings of words you don't know, but only if you know the meanings of the defining words. How many…

cs.CL2008

What It Feels Like To Hear Voices: Fond Memories of Julian Jaynes

Stevan Harnad

Julian Jaynes's profound humanitarian convictions not only prevented him from going to war, but would have prevented him from ever kicking a dog. Yet according to his theory, not o…