activity
20182023
most citedUnpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach

58 citations · 114 across the 15 of their papers we have counts for

collaborators
Showing 2018Show all

6 papers · 1 filter

cs.CL2018

Text Assisted Insight Ranking Using Context-Aware Memory Network

Qi Zeng, Liangchen Luo, Wenhao Huang +1

Extracting valuable facts or informative summaries from multi-dimensional tables, i.e. insight mining, is an important task in data analysis and business intelligence. However, ran…

cs.CL2018★ 4 cited

Learning Personalized End-to-End Goal-Oriented Dialog

Liangchen Luo, Wenhao Huang, Qi Zeng +2

Most existing works on dialog systems only consider conversation content while neglecting the personality of the user the bot is interacting with, which begets several unsolved iss…

cs.CL2018★ 6 cited

An Auto-Encoder Matching Model for Learning Utterance-Level Semantic Dependency in Dialogue Generation

Liangchen Luo, Jingjing Xu, Junyang Lin +2

Generating semantically coherent responses is still a major challenge in dialogue generation. Different from conventional text generation tasks, the mapping between inputs and resp…

cs.CL2018★ 4 cited

A Skeleton-Based Model for Promoting Coherence Among Sentences in Narrative Story Generation

Jingjing Xu, Xuancheng Ren, Yi Zhang +3

Narrative story generation is a challenging problem because it demands the generated sentences with tight semantic connections, which has not been well studied by most existing gen…

cs.CL2018★ 1 cited

Review-Driven Multi-Label Music Style Classification by Exploiting Style Correlations

Guangxiang Zhao, Jingjing Xu, Qi Zeng +1

This paper explores a new natural language processing task, review-driven multi-label music style classification. This task requires the system to identify multiple styles of music…

cs.CL2018★ 58 cited

Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach

Jingjing Xu, Xu Sun, Qi Zeng +4

The goal of sentiment-to-sentiment "translation" is to change the underlying sentiment of a sentence while keeping its content. The main challenge is the lack of parallel data. To…