21 citations · 74 across the 17 of their papers we have counts for
4 papers · 1 filter
Compositional Generalization Across Distributional Shifts with Sparse Tree Operations
Paul Soulos, Henry Conklin, Mattia Opper +3
Neural networks continue to struggle with compositional generalization, and this issue is exacerbated by a lack of massive pre-training. One successful approach for developing neur…
Mechanisms of Symbol Processing for In-Context Learning in Transformer Networks
Paul Smolensky, Roland Fernandez, Zhenghao Herbert Zhou +3
Large Language Models (LLMs) have demonstrated impressive abilities in symbol processing through in-context learning (ICL). This success flies in the face of decades of critiques a…
Neurocompositional computing: From the Central Paradox of Cognition to a new generation of AI systems
Paul Smolensky, R. Thomas McCoy, Roland Fernandez +2
What explains the dramatic progress from 20th-century to 21st-century AI, and how can the remaining limitations of current AI be overcome? The widely accepted narrative attributes…
Learning and analyzing vector encoding of symbolic representations
Roland Fernandez, Asli Celikyilmaz, Rishabh Singh +1
We present a formal language with expressions denoting general symbol structures and queries which access information in those structures. A sequence-to-sequence network processing…