Precisely the Point: Adversarial Augmentations for Faithful and
Informative Text Generation

Precisely the Point: Adversarial Augmentations for Faithful and Informative Text Generation

22 October 2022

Sujian Li

Papers citing "Precisely the Point: Adversarial Augmentations for Faithful and Informative Text Generation"

7 / 7 papers shown

Title
WeCheck: Strong Factual Consistency Checker via Weakly Supervised Learning Wenhao Wu Wei Li Xinyan Xiao Jiachen Liu Sujian Li Yajuan Lv HILM 26 4 0 20 Dec 2022
Increasing Faithfulness in Knowledge-Grounded Dialogue with Controllable Features Hannah Rashkin David Reitter Gaurav Singh Tomar Dipanjan Das 167 101 0 14 Jul 2021
Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics Artidoro Pagnoni Vidhisha Balachandran Yulia Tsvetkov HILM 231 305 0 27 Apr 2021
Towards Faithfulness in Open Domain Table-to-text Generation from an Entity-centric View Tianyu Liu Xin Zheng Baobao Chang Zhifang Sui 124 35 0 17 Feb 2021
Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints Zhenyi Wang Xiaoyang Wang Bang An Dong Yu Changyou Chen LMTD 168 84 0 03 May 2020
FreeLB: Enhanced Adversarial Training for Natural Language Understanding Chen Zhu Yu Cheng Zhe Gan S. Sun Tom Goldstein Jingjing Liu AAML 223 438 0 25 Sep 2019
Teaching Machines to Read and Comprehend Karl Moritz Hermann Tomás Kociský Edward Grefenstette L. Espeholt W. Kay Mustafa Suleyman Phil Blunsom 175 3,510 0 10 Jun 2015