Search Results for author:
Found 3 papers, 0 papers with code
The Natural Language Pipeline, Neural Text Generation and Explainability
End-to-end encoder-decoder approaches to data-to-text generation are often black boxes whose predictions are difficult to explain.
Entity-Based Semantic Adequacy for Data-to-Text Generation
While powerful pre-trained language models have improved the fluency of text generation models, semantic adequacy -the ability to generate text that is semantically faithful to the input- remains an unsolved issue.
Question Generation in Knowledge-Driven Dialog: Explainability and Evaluation
We explore question generation in the context of knowledge-grounded dialogs focusing on explainability and evaluation.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
