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Educational Research on Artificial Intelligence - ISSN 2695-6411

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  • Inaccessibility 7 de November de 2025
    IMG_9811 – CC-BY-NC by Eddie Lawrance Day 7 of 30DayMapChallenge: « Accessibility » (previously). Well, let us be rebellious and instead seek inaccessibility; more precisely the pole of inaccessibility of France (the Hexagon... Continue reading: Inaccessibility
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    Learn how to evaluate synthetic data quality using the Maximum Similarity Test — a simple, quantitative approach for assessing fidelity, utility, and privacy in synthetic datasets. The post Evaluating Synthetic Data — The Million Dollar Question appeared first on Towards Data Science.
    Andrew Skabar

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  • Ground-Truth Subgraphs for Better Training and Evaluation of Knowledge Graph Augmented LLMs 7 de November de 2025
    arXiv:2511.04473v1 Announce Type: cross Abstract: Retrieval of information from graph-structured knowledge bases represents a promising direction for improving the factuality of LLMs. While various solutions have been proposed, a comparison of methods is difficult due to the lack of challenging QA datasets with ground-truth targets for graph retrieval. We present SynthKGQA, a framework for generating […]

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🚷 #Autonomous #Vehicles


#Artificial #Reality

#Datascience


🔴 #Cybersecurity


#Frameworks

#Law and #Ethics


#MachineLearning

Natural Language Processing #NLP


🔘 #Medicine


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© 2019-2022 | La Biblia de la IA – The Bible of AI™ | The license except specific licensing: Creative Commons (CC BY-SA 4.0) | ISSN 2695-6411
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