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Found 3 papers, 1 papers with code
PLAtE: A Large-scale Dataset for List Page Web Extraction
Recently, neural models have been leveraged to significantly improve the performance of information extraction from semi-structured websites.
Generating Self-Contained and Summary-Centric Question Answer Pairs via Differentiable Reward Imitation Learning
Motivated by suggested question generation in conversational news recommendation systems, we propose a model for generating question-answer pairs (QA pairs) with self-contained, summary-centric questions and length-constrained, article-summarizing answers.
Evaluating the Tradeoff Between Abstractiveness and Factuality in Abstractive Summarization
Neural models for abstractive summarization tend to generate output that is fluent and well-formed but lacks semantic faithfulness, or factuality, with respect to the input documents.
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