activity
20182021
most citedGenerate, Delete and Rewrite: A Three-Stage Framework for Improving Persona Consistency of Dialogue Generation

14 citations · 24 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2021

Sketch and Customize: A Counterfactual Story Generator

Changying Hao, Liang Pang, Yanyan Lan +3

Recent text generation models are easy to generate relevant and fluent text for the given text, while lack of causal reasoning ability when we change some parts of the given text.…

cs.CL202110 cited

Non-Autoregressive Text Generation with Pre-trained Language Models

Yixuan Su, Deng Cai, Yan Wang +4

Non-autoregressive generation (NAG) has recently attracted great attention due to its fast inference speed. However, the generation quality of existing NAG models still lags behind…

cs.CL202014 cited

Generate, Delete and Rewrite: A Three-Stage Framework for Improving Persona Consistency of Dialogue Generation

Haoyu Song, Yan Wang, Wei-Nan Zhang +2

Maintaining a consistent personality in conversations is quite natural for human beings, but is still a non-trivial task for machines. The persona-based dialogue generation task is…

cs.CL2018

Translating a Math Word Problem to an Expression Tree

Lei Wang, Yan Wang, Deng Cai +2

Sequence-to-sequence (SEQ2SEQ) models have been successfully applied to automatic math word problem solving. Despite its simplicity, a drawback still remains: a math word problem c…

cs.CL2018

Skeleton-to-Response: Dialogue Generation Guided by Retrieval Memory

Deng Cai, Yan Wang, Victoria Bi +4

For dialogue response generation, traditional generative models generate responses solely from input queries. Such models rely on insufficient information for generating a specific…