Constructing Highly Inductive Contexts for Dialogue Safety through
Controllable Reverse Generation

Constructing Highly Inductive Contexts for Dialogue Safety through Controllable Reverse Generation

4 December 2022

Jiale Cheng

Lifeng Shang

Papers citing "Constructing Highly Inductive Contexts for Dialogue Safety through Controllable Reverse Generation"

6 / 6 papers shown

Title
CMD: a framework for Context-aware Model self-Detoxification Zecheng Tang Keyan Zhou Juntao Li Yuyang Ding Pinzheng Wang Bowen Yan Minzhang MU 18 5 0 16 Aug 2023
Automatically Exposing Problems with Neural Dialog Models Dian Yu Kenji Sagae 15 9 0 14 Sep 2021
Exploring Prompt-based Few-shot Learning for Grounded Dialog Generation Chujie Zheng Minlie Huang 51 44 0 14 Sep 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 278 3,784 0 18 Apr 2021
Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP Timo Schick Sahana Udupa Hinrich Schütze 257 374 0 28 Feb 2021
The Woman Worked as a Babysitter: On Biases in Language Generation Emily Sheng Kai-Wei Chang Premkumar Natarajan Nanyun Peng 204 607 0 03 Sep 2019