Papers by M. Willis Monroe

1 papers
Compositionality of Complex Graphemes in the Undeciphered Proto-Elamite Script using Image and Text Embedding Models (2021.findings-acl)

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Challenge: a language model over sign images produces more interpretable results than a model over text . a new language model is developed to abstract from human annotators .
Approach: They propose a language modeling architecture which operates over sequences of images or over multimodal sequences with associated labels.
Outcome: The proposed language model can interpret signs in the undeciphered proto-Elamite script . it also provides a novel way to abstract away from biases introduced by human annotators.

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