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Found 5 papers, 1 papers with code
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics.
Ranked #1 on
Data-to-Text Generation
on WebNLG ru
Abstractive Text Summarization
Cross-Lingual Abstractive Summarization
+5
UMSIForeseer at SemEval-2020 Task 11: Propaganda Detection by Fine-Tuning BERT with Resampling and Ensemble Learning
We describe our participation at the SemEval 2020 {``}Detection of Propaganda Techniques in News Articles{''} - Techniques Classification (TC) task, designed to categorize textual fragments into one of the 14 given propaganda techniques.
Neural Language Generation: Formulation, Methods, and Evaluation
Nevertheless, there is no standard way to assess the quality of text produced by these generative models, which constitutes a serious bottleneck towards the progress of the field.
Explainable Prediction of Text Complexity: The Missing Preliminaries for Text Simplification
Text simplification reduces the language complexity of professional content for accessibility purposes.
Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation
We conduct a large-scale, systematic study to evaluate the existing evaluation methods for natural language generation in the context of generating online product reviews.
