Apr 16, 2021 · Using natural language explanations, we supervise the model's attention weights to encourage more attention to be paid to the words present in ...
Sep 5, 2024 · Training with the human explanations encourages models to attend more broadly across the sentences, paying more attention to words in the ...
Using natural language explanations, we supervise a model's attention weights to encourage more attention to be paid to the words present in these explanations.
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Dec 4, 2018 · The Stanford Natural Language Inference dataset is extended with an additional layer of human-annotated natural language explanations of the entailment ...
In this work, we extend the Stanford Natural Language Inference dataset with an additional layer of human-annotated natural language explanations of the ...
Analysis of the model indi- cates that human explanations encourage increased attention on the important words, with more attention paid to words in the premise ...
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Using natural language explanations, supervised models are taught how a human would approach the NLI task, in order to learn features that will generalise ...
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In this work, we extend the Stanford Natural Language Inference dataset with an additional layer of human-annotated natural language explanations of the ...
Natural language inference (NLI) is the task of determining whether a "hypothesis" is true (entailment), false (contradiction), or undetermined (neutral) given ...
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We denote the human-provided gold explanation for the correct predictions as tg. S denotes a module which predicts label scores. The true label for an example ...
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