When transformer models see easy component examples before a harder combined math problem in one prompt, they solve unseen versions of the combined problem and store intermediate steps internally, unlike models trained only on combined examples.
Real-world visual statistics and infants’ first-learned object names.Philosophical Transactions of the Royal Society B: Biological Sciences, 372(1711):20160055, 2017
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Distinct Computations Emerge From Compositional Curricula in In-Context Learning
When transformer models see easy component examples before a harder combined math problem in one prompt, they solve unseen versions of the combined problem and store intermediate steps internally, unlike models trained only on combined examples.