4 citations · 4 across the 1 of their papers we have counts for
4 papers · 1 filter
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.…
Evaluating the Tradeoff Between Abstractiveness and Factuality in Abstractive Summarization
Markus Dreyer, Mengwen Liu, Feng Nan +2
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 documen…
Transductive Learning for Abstractive News Summarization
Arthur Bražinskas, Mengwen Liu, Ramesh Nallapati +2
Pre-trained and fine-tuned news summarizers are expected to generalize to news articles unseen in the fine-tuning (training) phase. However, these articles often contain specifics,…
Multi-Task Networks With Universe, Group, and Task Feature Learning
Shiva Pentyala, Mengwen Liu, Markus Dreyer
We present methods for multi-task learning that take advantage of natural groupings of related tasks. Task groups may be defined along known properties of the tasks, such as task d…