activity
20182021
most citedContinuous Conditional Generative Adversarial Networks (cGAN) with Generator Regularization

5 citations · 7 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG20215 cited

Continuous Conditional Generative Adversarial Networks (cGAN) with Generator Regularization

Yufeng Zheng, Yunkai Zhang, Zeyu Zheng

Conditional Generative Adversarial Networks are known to be difficult to train, especially when the conditions are continuous and high-dimensional. To partially alleviate this diff…

cs.CL2020

Logic2Text: High-Fidelity Natural Language Generation from Logical Forms

Zhiyu Chen, Wenhu Chen, Hanwen Zha +4

Previous works on Natural Language Generation (NLG) from structured data have primarily focused on surface-level descriptions of record sequences. However, for complex structured d…

cs.LG20192 cited

You May Not Need Order in Time Series Forecasting

Yunkai Zhang, Qiao Jiang, Shurui Li +3

Time series forecasting with limited data is a challenging yet critical task. While transformers have achieved outstanding performances in time series forecasting, they often requi…

cs.CL2019

TabFact: A Large-scale Dataset for Table-based Fact Verification

Wenhu Chen, Hongmin Wang, Jianshu Chen +5

The problem of verifying whether a textual hypothesis holds based on the given evidence, also known as fact verification, plays an important role in the study of natural language u…

stat.ML2018

Exploration of Numerical Precision in Deep Neural Networks

Zhaoqi Li, Yu Ma, Catalina Vajiac +1

Reduced numerical precision is a common technique to reduce computational cost in many Deep Neural Networks (DNNs). While it has been observed that DNNs are resilient to small erro…