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cs.LG2026
Spatial Induction Heads: In-Context Learning of Multidimensional Cellular Automata
Kimia Kazemian, Menghan Xu, John Thickstun +1
Induction heads provide a mechanistic account of in-context learning in sequential data, but existing theory largely assumes that the context relevant to a prediction forms a conti…
cs.IR2026
Credit-assigned Policy Gradient for Early Stage Retrieval in Two-stage Ranking
Haruka Kiyohara, Mihaela Curmei, Ariel Evnine +7
Large-scale search, recommendation, and retrieval-augmented generation (RAG) systems typically employ a two-stage architecture: an early-stage ranker (ESR) generates a candidate se…
eess.SY2026
Recommender Systems as Control Systems
Giulia De Pasquale, Sarah Dean, Paolo Frasca
We propose a control-theoretic interpretation of recommender systems and use this perspective to analyze how fairness interventions shape long-term system behavior. Fairness concer…