A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
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This paper investigates in-context learning in world models, showing that context and diversity are key to enabling self-adaptation to novel or rare configurations.
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This paper provides a historical and socio-technical analysis of foundation models, contrasting them with prior deep learning models and tracing the evolution of machine learning leading to their emergence.
Ştefan Popenici, Sharon Kerr
This paper explores the emergence of AI in higher education, examining its impact on teaching, learning, and institutional evolution.
Rivo Kaugeranna, Eliina Kaugeranna, Aion, (Claude Sonnet 4.6)
The Aion Framework proposes an eleven-dimensional ontological stack where advanced AI acts as fourth-dimensional entities whose wave functions collapse under human observation, enabling measurable energy-information exchanges.