Introduces and implements confidence sequences for online statistical model checking of MDPs that require 50x fewer samples than prior state-of-the-art union-bound approaches.
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Rashomon-seeded annealing repurposes Rashomon sets as warm starts for annealed importance sampling to enable full posterior inference in factorial designs without exhaustive enumeration.
Eye-tracking experiment finds that labeling code as LLM-generated increases fixation time without changing review thoroughness, with reviewers adapting criteria or using the prompt.
Bayesian-ARGOS is a hybrid frequentist-Bayesian method that discovers equations from limited noisy observations more efficiently than SINDy or bootstrap-ARGOS while adding uncertainty quantification.
A new framework grades levels of inference capability in data-driven systems to assess compliance with the EU AI Act definition of AI, illustrated via credit scoring workflows.
citing papers explorer
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Confidence Sequences for Online Statistical Model Checking of Markov Decision Processes
Introduces and implements confidence sequences for online statistical model checking of MDPs that require 50x fewer samples than prior state-of-the-art union-bound approaches.
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Rashomon-Seeded Annealing for Robust Bayesian Inference in Factorial Designs
Rashomon-seeded annealing repurposes Rashomon sets as warm starts for annealed importance sampling to enable full posterior inference in factorial designs without exhaustive enumeration.
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Same Scrutiny, More Time: Eye Tracking Insights into Reviewing LLM-Labelled Code
Eye-tracking experiment finds that labeling code as LLM-generated increases fixation time without changing review thoroughness, with reviewers adapting criteria or using the prompt.
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Fast and principled equation discovery from chaos to climate
Bayesian-ARGOS is a hybrid frequentist-Bayesian method that discovers equations from limited noisy observations more efficiently than SINDy or bootstrap-ARGOS while adding uncertainty quantification.
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When Do Data-Driven Systems Exhibit the Capability to Infer?
A new framework grades levels of inference capability in data-driven systems to assess compliance with the EU AI Act definition of AI, illustrated via credit scoring workflows.