AI RESEARCH
Genomic Next-Token Predictors are In-Context Learners
arXiv CS.LG
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ArXi:2511.12797v3 Announce Type: replace In-context learning (ICL) -- the capacity of a model to infer and apply abstract patterns from examples provided within its input -- has been extensively studied in large language models trained for next-token prediction on human text. In fact, prior work often attributes this emergent behavior to distinctive statistical properties in human language. This raises a fundamental question: can ICL arise organically in other sequence domains purely through large-scale predictive.