21 citations · 58 across the 11 of their papers we have counts for
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cs.CL2024
Pruning Literals for Highly Efficient Explainability at Word Level
Rohan Kumar Yadav, Bimal Bhattarai, Abhik Jana +2
Designing an explainable model becomes crucial now for Natural Language Processing(NLP) since most of the state-of-the-art machine learning models provide a limited explanation for…
cs.LG2024★ 1 cited
Exploring Effects of Hyperdimensional Vectors for Tsetlin Machines
Vojtech Halenka, Ahmed K. Kadhim, Paul F. A. Clarke +5
Tsetlin machines (TMs) have been successful in several application domains, operating with high efficiency on Boolean representations of the input data. However, Booleanizing compl…