3 papers
cs.IR2026
STORM: Stepwise Token Optimization with Reward-Guided Beam Search
Arthur Satouf, Giulio D'Erasmo, Yuxuan Zong +3
Modern retrieval increasingly relies on dense and learned-sparse neural models that are effective but require encoding the entire corpus into a specialized index, rebuilt whenever…
cs.IR2025
Rational Retrieval Acts: Leveraging Pragmatic Reasoning to Improve Sparse Retrieval
Arthur Satouf, Gabriel Ben Zenou, Benjamin Piwowarski +2
Current sparse neural information retrieval (IR) methods, and to a lesser extent more traditional models such as BM25, do not take into account the document collection and the comp…
stat.ML2020
Challenging common bolus advisor for self-monitoring type-I diabetes patients using Reinforcement Learning
Frédéric Logé, Erwan Le Pennec, Habiboulaye Amadou-Boubacar
Patients with diabetes who are self-monitoring have to decide right before each meal how much insulin they should take. A standard bolus advisor exists, but has never actually been…