11 citations · 18 across the 5 of their papers we have counts for
6 papers
R2D2: Robust Data-to-Text with Replacement Detection
Linyong Nan, Lorenzo Jaime Yu Flores, Yilun Zhao +4
Unfaithful text generation is a common problem for text generation systems. In the case of Data-to-Text (D2T) systems, the factuality of the generated text is particularly crucial…
BRIO: Bringing Order to Abstractive Summarization
Yixin Liu, Pengfei Liu, Dragomir Radev +1
Abstractive summarization models are commonly trained using maximum likelihood estimation, which assumes a deterministic (one-point) target distribution in which an ideal model wil…
DataLab: A Platform for Data Analysis and Intervention
Yang Xiao, Jinlan Fu, Weizhe Yuan +5
Despite data's crucial role in machine learning, most existing tools and research tend to focus on systems on top of existing data rather than how to interpret and manipulate data.…
SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization
Yixin Liu, Pengfei Liu
In this paper, we present a conceptually simple while empirically powerful framework for abstractive summarization, SimCLS, which can bridge the gap between the learning objective…
RefSum: Refactoring Neural Summarization
Yixin Liu, Zi-Yi Dou, Pengfei Liu
Although some recent works show potential complementarity among different state-of-the-art systems, few works try to investigate this problem in text summarization. Researchers in…
ExplainaBoard: An Explainable Leaderboard for NLP
Pengfei Liu, Jinlan Fu, Yang Xiao +7
With the rapid development of NLP research, leaderboards have emerged as one tool to track the performance of various systems on various NLP tasks. They are effective in this goal…