AI RESEARCH
Transformer See, Transformer Do: Copying as an Intermediate Step in Learning Analogical Reasoning
arXiv CS.LG
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ArXi:2604.06501v1 Announce Type: new Analogical reasoning is a hallmark of human intelligence, enabling us to solve new problems by transferring knowledge from one situation to another. Yet, developing artificial intelligence systems capable of robust human-like analogical reasoning has proven difficult. In this work, we train transformers using Meta-Learning for Compositionality (MLC) on an analogical reasoning task (letter-string analogies) and assess their generalization capabilities.