1,846 research outputs found

    Three-dimensional shape descriptors and matching procedures

    Get PDF
    Shape descriptors are used to identify objects in the same way that human fingerprints are used to identify people. Features of an object are extracted by applying functions to the digital representation of the object. These features are structured as a vector which is known as the shape descriptor (feature vector) of that object. The objective when constructing a shape descriptor is to find functions that will yield shape descriptors that can be used to uniquely identify or at least classify an object. A measure of similarity is required to identify or classify an object. The similarity between two objects is computed by applying a distance function to the shape descriptors of the two objects. The objective of this paper is to examine two of the possible techniques in three-dimensional shape descriptor construction based on Fourier analysis, and to find a descriptor that is able to not only classify, but also identify objects

    Trapping LLM Hallucinations Using Tagged Context Prompts

    Full text link
    Recent advances in large language models (LLMs), such as ChatGPT, have led to highly sophisticated conversation agents. However, these models suffer from "hallucinations," where the model generates false or fabricated information. Addressing this challenge is crucial, particularly with AI-driven platforms being adopted across various sectors. In this paper, we propose a novel method to recognize and flag instances when LLMs perform outside their domain knowledge, and ensuring users receive accurate information. We find that the use of context combined with embedded tags can successfully combat hallucinations within generative language models. To do this, we baseline hallucination frequency in no-context prompt-response pairs using generated URLs as easily-tested indicators of fabricated data. We observed a significant reduction in overall hallucination when context was supplied along with question prompts for tested generative engines. Lastly, we evaluated how placing tags within contexts impacted model responses and were able to eliminate hallucinations in responses with 98.88% effectiveness.Comment: 13 pages, 3 Figures, 2 Table

    The Effect Of Breastfeeding On Child Development At 5 Years: A Cohort Study

    Get PDF
    Objective It is uncertain to what degree the relationship between breastfeeding and later cognitive development is a true biological effect, or is confounded by psychosocial factors. The study aim was to further investigate this relationship and the effect of duration of breast feeding on cognitive development. Methods A total of 3880 children were followed from birth. Breastfeeding duration was measured by questionnaire at 6 months of age and a Peabody Picture Vocabulary Test Revised (PPVT-R) was administered at 5 years. PPVT-R scores were adjusted for the effects of a large array of biological and psychosocial confounders. The relationship between breastfeeding and the mean PPVT-R scores were examined using analysis of variance and multiple linear regression. Results A strong positive relationship was demonstrated between breastfeeding and the PPVT-R scores with increasing scores with increased duration of breastfeeding. After adjusting for a wide range of biological and social factors, the adjusted mean for those breastfed for 6 months or more was 8.2 points higher for females and 5.8 points for males when compared to those never breastfed. Conclusion These findings suggest a significant benefit to child development is conferred by breastfeeding and is related independently to longer periods of breastfeeding
    corecore