activity
20172020
most citedTopic-Guided Variational Autoencoders for Text Generation

56 citations · 151 across the 6 of their papers we have counts for

collaborators

12 papers

stat.ML202049 cited

GenDICE: Generalized Offline Estimation of Stationary Values

Ruiyi Zhang, Bo Dai, Lihong Li +1

An important problem that arises in reinforcement learning and Monte Carlo methods is estimating quantities defined by the stationary distribution of a Markov chain. In many real-w…

cs.CV20197 cited

Figure Captioning with Reasoning and Sequence-Level Training

Charles Chen, Ruiyi Zhang, Eunyee Koh +5

Figures, such as bar charts, pie charts, and line plots, are widely used to convey important information in a concise format. They are usually human-friendly but difficult for comp…

cs.CL201956 cited

Topic-Guided Variational Autoencoders for Text Generation

Wenlin Wang, Zhe Gan, Hongteng Xu +5

We propose a topic-guided variational autoencoder (TGVAE) model for text generation. Distinct from existing variational autoencoder (VAE) based approaches, which assume a simple Ga…

stat.ML20198 cited

Scalable Thompson Sampling via Optimal Transport

Ruiyi Zhang, Zheng Wen, Changyou Chen +1

Thompson sampling (TS) is a class of algorithms for sequential decision-making, which requires maintaining a posterior distribution over a model. However, calculating exact posteri…

cs.CL201923 cited

Improving Sequence-to-Sequence Learning via Optimal Transport

Liqun Chen, Yizhe Zhang, Ruiyi Zhang +7

Sequence-to-sequence models are commonly trained via maximum likelihood estimation (MLE). However, standard MLE training considers a word-level objective, predicting the next word…

cs.CL2018

Sequence Generation with Guider Network

Ruiyi Zhang, Changyou Chen, Zhe Gan +5

Sequence generation with reinforcement learning (RL) has received significant attention recently. However, a challenge with such methods is the sparse-reward problem in the RL trai…