55 citations · 75 across the 10 of their papers we have counts for
11 papers
NewsQs: Multi-Source Question Generation for the Inquiring Mind
Alyssa Hwang, Kalpit Dixit, Miguel Ballesteros +5
We present NewsQs (news-cues), a dataset that provides question-answer pairs for multiple news documents. To create NewsQs, we augment a traditional multi-document summarization da…
Background Summarization of Event Timelines
Adithya Pratapa, Kevin Small, Markus Dreyer
Generating concise summaries of news events is a challenging natural language processing task. While journalists often curate timelines to highlight key sub-events, newcomers to a…
Generating Summaries with Controllable Readability Levels
Leonardo F. R. Ribeiro, Mohit Bansal, Markus Dreyer
Readability refers to how easily a reader can understand a written text. Several factors affect the readability level, such as the complexity of the text, its subject matter, and t…
On Conditional and Compositional Language Model Differentiable Prompting
Jonathan Pilault, Can Liu, Mohit Bansal +1
Prompts have been shown to be an effective method to adapt a frozen Pretrained Language Model (PLM) to perform well on downstream tasks. Prompts can be represented by a human-engin…
Faithfulness-Aware Decoding Strategies for Abstractive Summarization
David Wan, Mengwen Liu, Kathleen McKeown +2
Despite significant progress in understanding and improving faithfulness in abstractive summarization, the question of how decoding strategies affect faithfulness is less studied.…
Efficient Few-Shot Fine-Tuning for Opinion Summarization
Arthur Bražinskas, Ramesh Nallapati, Mohit Bansal +1
Abstractive summarization models are typically pre-trained on large amounts of generic texts, then fine-tuned on tens or hundreds of thousands of annotated samples. However, in opi…