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In healthcare, a fluent answer can be less useful than a justified decision not to answer. This review examines how language models abstain when information is uncertain or when a response could be harmful. It distinguishes uncertainty-driven abstention from safety-driven refusal and finds that many…

Can language models help reviewers find methodological weaknesses in clinical-trial reports? This preprint tests fifteen models on documents containing deliberately inserted errors, first using reports from an earlier human-review experiment and then extending the task to 58 trials published in 2026. It examines detection scores,…

This systematic review examines how language-model agents are being used in cybersecurity, from penetration testing and threat intelligence to incident response. It classifies 59 studies published between January 2022 and April 2026 by security function, agent architecture, knowledge augmentation, human oversight and evaluation rigor. The…

How can a passenger understand why a self-driving car behaves unexpectedly? This study introduces the Concept-Wrapper Network (CW-Net), which connects a learned planner to human-readable concepts and examines whether explanations improve understanding of vehicle behaviour. Its evaluation combines private-track experiments with a real autonomous vehicle,…

Can a compact text encoder learn representations that agree with vision more closely than those of a much larger language model? This preprint investigates that question through a conditional mathematical theorem and experiments comparing Joint-Embedding Predictive Architectures (JEPAs) with next-token prediction. Its central proposal is…

Can a research agent tell when its own calculation has led it astray? In FrontierPhysics, physicists turned investigations from their own laboratories and research groups into 56 problems. An agent receives a brief, explores the literature, chooses a method and submits a manuscript alongside results…