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Found 3 papers, 2 papers with code
FENICE: Factuality Evaluation of summarization based on Natural language Inference and Claim Extraction
To address these shortcomings, we propose Factuality Evaluation of summarization based on Natural language Inference and Claim Extraction (FENICE), a more interpretable and efficient factuality-oriented metric.
Echoes from Alexandria: A Large Resource for Multilingual Book Summarization
In recent years, research in text summarization has mainly focused on the news domain, where texts are typically short and have strong layout features.
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Semantic Role Labeling Meets Definition Modeling: Using Natural Language to Describe Predicate-Argument Structures
One of the common traits of past and present approaches for Semantic Role Labeling (SRL) is that they rely upon discrete labels drawn from a predefined linguistic inventory to classify predicate senses and their arguments.
