Papers by Elijah Mayfield

2 papers
Why Attention is Not Explanation: Surgical Intervention and Causal Reasoning about Neural Models (2020.lrec-1)

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Challenge: a recent study finds brittleness in explanations obtained through attention mechanisms . a philosophy of science theory allows robust yet non-causal reasoning in explanation .
Approach: They propose to use philosophy of science to examine the state-of-the-art in explanation for NLP models . they argue that it is impossible to explain attention-based learning by attention mechanisms .
Outcome: The proposed model selection criteria are based on philosophy of science theories . the proposed model is based upon a model that is more explainable than a classical model .
Machine-Aided Annotation for Fine-Grained Proposition Types in Argumentation (2020.lrec-1)

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Challenge: a corpus of 2016 debates and commentary contains 4,648 argumentative propositions annotated with fine-grained proposition types.
Approach: They propose a machine learning-human workflow for annotating for four complex proposition types . they demonstrate with preliminary analysis of rhetorical strategies and structure in presidential debates .
Outcome: The proposed method can be used by technical researchers seeking more nuanced representations of argument . it can also be used to analyze rhetorical strategies and structure in presidential debates .

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