arxiv
PublishedJuly 27, 2026 at 4:00 AM
—neutral
Prior laundering: learned priors with inherited, undetectable overconfidence
Publisher summary· verbatim
arXiv:2607.21721v1 Announce Type: cross Abstract: Learned generative priors are increasingly used for ill-posed Bayesian inverse problems, their posterior uncertainty treated as earned from data. But training one requires truths, scarce in seismic and medical imaging, so the recourse is an archive o
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivA Consensus-Based Framework for Relative Preference Evaluation of Large Language Models6harxivProbing Latent Colombian Identity Inferences in Qwen2.5-7B with Natural Language Autoencoders6harxivData Quality over Capacity: Internalizing Documents into LoRA Adapters for Closed-Book QA6harxivEnjoy Your Talk: A Human-Centered Benchmark for Multi-Turn Dialogue with Decoupled User Simulation, Target Modeling, and Judging6hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗