519 citations · 530 across the 4 of their papers we have counts for
8 papers
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu +3
This paper surveys and organizes research works in a new paradigm in natural language processing, which we dub "prompt-based learning". Unlike traditional supervised learning, whic…
WikiAsp: A Dataset for Multi-domain Aspect-based Summarization
Hiroaki Hayashi, Prashant Budania, Peng Wang +3
Aspect-based summarization is the task of generating focused summaries based on specific points of interest. Such summaries aid efficient analysis of text, such as quickly understa…
What's New? Summarizing Contributions in Scientific Literature
Hiroaki Hayashi, Wojciech Kryściński, Bryan McCann +2
With thousands of academic articles shared on a daily basis, it has become increasingly difficult to keep up with the latest scientific findings. To overcome this problem, we intro…
GSum: A General Framework for Guided Neural Abstractive Summarization
Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi +2
Neural abstractive summarization models are flexible and can produce coherent summaries, but they are sometimes unfaithful and can be difficult to control. While previous studies a…
Findings of the Third Workshop on Neural Generation and Translation
Hiroaki Hayashi, Yusuke Oda, Alexandra Birch +5
This document describes the findings of the Third Workshop on Neural Generation and Translation, held in concert with the annual conference of the Empirical Methods in Natural Lang…
Linguistic Versus Latent Relations for Modeling Coherent Flow in Paragraphs
Dongyeop Kang, Hiroaki Hayashi, Alan W Black +1
Generating a long, coherent text such as a paragraph requires a high-level control of different levels of relations between sentences (e.g., tense, coreference). We call such a log…