Search Results for author:
Found 6 papers, 5 papers with code
Metadata Might Make Language Models Better
This paper discusses the benefits of including metadata when training language models on historical collections.
MapReader: A Computer Vision Pipeline for the Semantic Exploration of Maps at Scale
We present MapReader, a free, open-source software library written in Python for analyzing large map collections (scanned or born-digital).
Neural Language Models for Nineteenth-Century English
We present four types of neural language models trained on a large historical dataset of books in English, published between 1760-1900 and comprised of ~5. 1 billion tokens.
Living Machines: A study of atypical animacy
This paper proposes a new approach to animacy detection, the task of determining whether an entity is represented as animate in a text.
Words are Malleable: Computing Semantic Shifts in Political and Media Discourse
We propose an approach for detecting semantic shifts between different viewpoints--broadly defined as a set of texts that share a specific metadata feature, which can be a time-period, but also a social entity such as a political party.
