no code implementations • COLING (WANLP) 2020 • Ryan Muther, David Smith
We present our work on automatically detecting isnads, the chains of authorities for a re-port that serve as citations in hadith and other classical Arabic texts.
no code implementations • 29 Jun 2023 • Ryan Muther, David Smith
This paper explores new methods for locating the sources used to write a text, by fine-tuning a variety of language models to rerank candidate sources.
no code implementations • 31 Aug 2022 • Ryan Muther, David Smith
Unlike prior work, therefore, we seek to leverage the information that can be gained from looking at association networks of individuals derived from textual evidence in order to disambiguate names.
no code implementations • 31 Aug 2022 • Ryan Muther, David Smith
We examine the tradeoffs in model performance involved in choices of training sample and filter training and test data in heavily imbalanced token classification task and examine the relationship between the magnitude of these tradeoffs and the base rate of the phenomenon of interest.