Papers with NLP framework

4 papers
The Classical Language Toolkit: An NLP Framework for Pre-Modern Languages (2021.acl-demo)

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Challenge: Classical Language Toolkit (CLTK) is an NLP framework for pre-modern languages . authors say it assumes pre-existing living languages, neglecting important characteristics of non-spoken historical languages despite their existence .
Approach: The paper announces version 1.0 of the Classical Language Toolkit (CLTK) it is an NLP framework for pre-modern languages that uses assumptions specific to living languages . authors propose a modular processing pipeline that balances competing demands of algorithmic diversity with pre-configured defaults .
Outcome: The Classical Language Toolkit (CLTK) is a new NLP framework for pre-modern languages . the framework is based on the existing frameworks and is available for almost 20 languages - including models .
FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP (N19-4)

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Challenge: Existing approaches combine word embeddings with character-level features to model additional features such as subword structures and meaning ambiguity.
Approach: They present FLAIR, an NLP framework that enables embeddings of word and document data . they propose a hierarchical learning architecture that concatenates output states of a character-level CNN or RNN with the output states from a task data.
Outcome: The proposed framework hides embedding-specific engineering complexity and allows researchers to "mix and match" various embeddables with little effort.
To Protect and To Serve? Analyzing Entity-Centric Framing of Police Violence (2021.findings-emnlp)

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Challenge: a new study examines the media coverage of police violence in the United States by examining the framing of 82k news articles spanning 7k police killings.
Approach: They propose an NLP framework to measure entity-centric framing to understand media coverage on police violence in the United States in a new police violence frames corpus of 82k news articles spanning 7k police killings.
Outcome: The proposed framework reveals significant differences in the way liberal and conservative news sources frame both the issue of police violence and the entities involved.
Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings (N19-1)

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Challenge: a new framework for studying political polarization in social media is needed to understand how group divisions manifest in language.
Approach: They propose to cluster tweet embeddings to uncover four dimensions of political polarization in social media . their results apply existing lexical methods to analyze 4.4M tweets on 21 mass shootings .
Outcome: The proposed framework generates more cohesive topics than traditional models.

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