Automatic Detection of Generated Text is Easiest when Humans are Fooled

2 November 2019

Papers citing "Automatic Detection of Generated Text is Easiest when Humans are Fooled"

6 / 56 papers shown

Title
Rethinking Search: Making Domain Experts out of Dilettantes Donald Metzler Yi Tay Dara Bahri Marc Najork LRM 38 46 0 05 May 2021
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers Krishna Pillutla Swabha Swayamdipta Rowan Zellers John Thickstun Sean Welleck Yejin Choi Zaïd Harchaoui 42 343 0 02 Feb 2021
Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hiding Sahar Abdelnabi Mario Fritz WaLM 28 89 0 07 Sep 2020
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 77 40,200 0 28 May 2020
Adversarial Evaluation of Dialogue Models Anjuli Kannan Oriol Vinyals AAML ALM 141 76 0 27 Jan 2017
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,748 0 26 Sep 2016