21 citations · 63 across the 37 of their papers we have counts for
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cs.AI2026
Estimating Great Expectations Under Autoregressive Language Models with Potentials
Francesco I. Re, Shubhangi Ghosh, Tim Vieira +1
Many applications of language models require estimating the expectation of a test functional under the model. Obtaining precise estimates can be computationally expensive. We show…
cs.AI2026
Learning to Reason Efficiently with A* Post-Training
Andreas Opedal, Francesco Ignazio Re, Abulhair Saparov +3
Many applications of large language models (LLMs) require deductive reasoning, yet models frequently produce incorrect or redundant inference steps. We frame natural language infer…