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cs.LG2026
Online LLM Personalization from Pairwise Preferences Across Users
Romain Puech, Georgy Salakhutdinov, Dimitris Bertsimas
Large language models can answer the same question in different styles, but users' preferred styles are hidden and vary across users and questions. We study inference-time personal…
stat.AP2026
Observing the unobserved confounding through its effects: toward randomized trial-like estimates from real-world survival data
Vasiliki Stoumpou, Dimitris Bertsimas, Samuel Singer +1
Background: Randomized controlled trials (RCTs) are costly, time-consuming, and often infeasible, while treatment-effect estimation from observational data is limited by unobserved…