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Posterior Ontology Memory (POM) models uncertainty in the vocabulary used by a symbolic memory, rather than assuming that its semantic schema is fixed. It treats mappings from surface predicates to latent semantic categories as uncertain and carries that uncertainty into prediction. The model combines a partition prior...
Background. RewardBench 2 aggregates pairwise preference accuracy across heterogeneous task families (factuality, instruction following, safety, and others). A single leaderboard score can mask systematic subset specialization, yet standard benchmark reporting rarely tests whether accuracy is independent of task catego...
Although LLM-based benchmark ratings can approximate expert judgments and reduce the need for labor-intensive human triple coding, limitations remain regarding cost, genre- and task specificity, and sensitivity to text presentation and student grade level—factors that constrain immediate classroom use, particularly for...
Overall, infrared thermography was used primarily as a non-invasive, adjunctive, and complementary imaging method to document skin-surface temperature distribution and thermal patterns in occupational contexts, and may contribute to multidisciplinary clinical assessment and decision-making.
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RadTechBERT with BPE_32K outperformed baselines in many subjects, with more than a twofold improvement in radiation safety management and radiation measurement relative to the strongest baseline, while gains were smaller in subjects having substantial overlap with general medicine, and Wikipedia mixing did not yield co...
Relational and information-based descriptions of reality have been explored in many domains, from relational readings of quantum mechanics to proposals that physical phenomena arise from the organization of information. This paper approaches the same questions from an unexpected side: sustained interaction with a large...
Using standardized oracle inputs and Cohen’s κ, it is found that, within the ranges tested, the major paradigms achieved comparable accuracy, and the field’s near-term gains lie in strengthening infrastructure—prioritizing tool accessibility, standardized evaluation, and robustness to pipeline variation.
Ophthalmology training requires visual interpretation, procedural skill, and supervised clinical reasoning, but trainee volume, faculty availability, and case mix constrain education. AI-enabled tools may support scalable instruction, assessment, and feedback. To evaluate AI-enabled interventions for improving ophthalm...
Executive Summary This work approaches the problem of selectively forgetting knowledge from a large language model (LLM) for the purposes of safety, copyright, security, or otherwise. Also known as machine unlearning, this entails training a model to forget certain elements of the dataset on which it was trained. Unlea...
In adults with primary hypertension, greater CMB burden was associated with MCI and selected cognitive domains, whereas cognitive performance did not differ according to CMB location, and prospective validation is required before clinical application.
Large language models (LLMs) are increasingly proposed as automated test generators, yet small, fully reproducible measurements with current-generation models remain rare in the open literature. We report a controlled study in which four configurations of the GPT-5 model family—gpt-5-nano, gpt-5-mini, gpt-5.4, and gpt-...
Ozone therapy is frequently promoted as a versatile and minimally invasive medical intervention purported to exert a broad range of biological effects, including anti-inflammatory, antimicrobial, immunomodulatory, and regenerative actions. These claims have led to its application across diverse clinical domains, such a...
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