Results 111 to 120 of about 34,824 (243)
Human tests for machine models: What lies “Beyond the Imitation Game”?
Abstract Benchmarking large language models (LLMs) is a key practice for evaluating their capabilities and risks. This paper considers the development of “BIG Bench,” a crowdsourced benchmark designed to test LLMs “Beyond the Imitation Game.” Drawing on linguistic anthropological and ethnographic analysis of the project's GitHub repository, we examine ...
Noya Kohavi, Anna Weichselbraun
wiley +1 more source
A Graph-Based Algorithm for Computing Matrix Elements of Arbitrary Operators between Configuration State Functions. [PDF]
Fdez Galván I, Rooein M, Lindh R.
europepmc +1 more source
Bridging Disciplines to Form a New One: The Emergence of Forensic Genetic Genealogy. [PDF]
Glynn CL.
europepmc +1 more source
Māori Data Sovereignty and Māori Data Governance are articulationsand expressions of our Māori rights to be self‐determining as sovereign peoples. Over the last decade, there has been considerable growth in scholarship, theorising and advocacy around Māori Data Sovereignty with a number of frameworks, models and sets of principles developed ...
Paula Toko King +9 more
wiley +1 more source
Evaluating the phylogenetic signal of morphosyntax. [PDF]
Sleeman R +6 more
europepmc +1 more source
Aotearoa New Zealand has one of the highest rates of anxiety and depression globally, with Māori and Pacific groups carrying the greatest burden. We need to better understand the driving factors to improve the availability and flexibility of our treatment pathways.
Olivia K. Harrison +24 more
wiley +1 more source
Neighbors and relatives: How do speech embeddings reflect linguistic connections across the world? [PDF]
Törö T, Suni A, Šimko J.
europepmc +1 more source
Abstract This study investigates species boundaries in the lichen genus Arctomia (Arctomiaceae, Ascomycota) using an integrative approach combining molecular phylogenetics, full Bayesian population delimitation, heuristic and model‐based species delimitation, and supervised machine learning applied to morphological data.
Stefan Ekman +2 more
wiley +1 more source

