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Found 8 papers, 5 papers with code
An Analysis of Natural Language Inference Benchmarks through the Lens of Negation
Negation is underrepresented in existing natural language inference benchmarks.
Interpreting Indirect Answers to Yes-No Questions in Multiple Languages
Experimental results demonstrate that monolingual fine-tuning is beneficial if training data can be obtained via distant supervision for the language of interest (5 languages).
Leveraging Affirmative Interpretations from Negation Improves Natural Language Understanding
Inspired by the fact that understanding a negated statement often requires humans to infer affirmative interpretations, in this paper we show that doing so benefits models for three natural language understanding tasks.
Natural Language Inference
Natural Language Understanding
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A Question-Answer Driven Approach to Reveal Affirmative Interpretations from Verbal Negations
We first cast the problem of revealing affirmative interpretations from negations as a natural language inference (NLI) classification task.
An Analysis of Negation in Natural Language Understanding Corpora
This paper analyzes negation in eight popular corpora spanning six natural language understanding tasks.
It's not a Non-Issue: Negation as a Source of Error in Machine Translation
As machine translation (MT) systems progress at a rapid pace, questions of their adequacy linger.
Smart Weather Forecasting Using Machine Learning:A Case Study in Tennessee
Furthermore, we show that it is beneficial to leverage the weather station data from multiple neighboring areas over the data of only the area for which weather forecasting is being performed.
Predicting the Focus of Negation: Model and Error Analysis
The focus of a negation is the set of tokens intended to be negated, and a key component for revealing affirmative alternatives to negated utterances.
