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Found 4 papers, 1 papers with code
Document Retrieval and Claim Verification to Mitigate COVID-19 Misinformation
The current vogue is to employ manual fact-checkers to verify claims to combat this avalanche of misinformation.
Identifying causal relations in tweets using deep learning: Use case on diabetes-related tweets from 2017-2021
A cause-effect-tweet dataset was manually labeled and used to train 1) a fine-tuned Bertweet model to detect causal sentences containing a causal association 2) a CRF model with BERT based features to extract possible cause-effect associations.
Template Filling for Controllable Commonsense Reasoning
To enable better controllability, we propose to study the commonsense reasoning as a template filling task (TemplateCSR) -- where the language models fills reasoning templates with the given constraints as control factors.
MIMICause: Representation and automatic extraction of causal relation types from clinical notes
This will enhance healthcare providers' ability to identify aspects of a patient's story communicated in the clinical notes and help make more informed decisions.
