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20162021
most citedEfficient Character-level Document Classification by Combining Convolution and Recurrent Layers

171 citations · 240 across the 9 of their papers we have counts for

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Showing cs.CLShow all

7 papers · 1 filter

cs.CL2021★ 16 cited

On Hallucination and Predictive Uncertainty in Conditional Language Generation

Yijun Xiao, William Yang Wang

Despite improvements in performances on different natural language generation tasks, deep neural models are prone to hallucinating facts that are incorrect or nonexistent. Differen…

cs.CL2020★ 5 cited

Why Neural Machine Translation Prefers Empty Outputs

Xing Shi, Yijun Xiao, Kevin Knight

We investigate why neural machine translation (NMT) systems assign high probability to empty translations. We find two explanations. First, label smoothing makes correct-length tra…

cs.CL2019★ 1 cited

Text Modeling with Syntax-Aware Variational Autoencoders

Yijun Xiao, William Yang Wang

Syntactic information contains structures and rules about how text sentences are arranged. Incorporating syntax into text modeling methods can potentially benefit both representati…

cs.CL2018★ 15 cited

Quantifying Uncertainties in Natural Language Processing Tasks

Yijun Xiao, William Yang Wang

Reliable uncertainty quantification is a first step towards building explainable, transparent, and accountable artificial intelligent systems. Recent progress in Bayesian deep lear…

cs.CL2018★ 8 cited

Implicit Regularization of Stochastic Gradient Descent in Natural Language Processing: Observations and Implications

Deren Lei, Zichen Sun, Yijun Xiao +1

Deep neural networks with remarkably strong generalization performances are usually over-parameterized. Despite explicit regularization strategies are used for practitioners to avo…

cs.CL2018★ 14 cited

Dirichlet Variational Autoencoder for Text Modeling

Yijun Xiao, Tiancheng Zhao, William Yang Wang

We introduce an improved variational autoencoder (VAE) for text modeling with topic information explicitly modeled as a Dirichlet latent variable. By providing the proposed model t…

cs.CL2016★ 171 cited

Efficient Character-level Document Classification by Combining Convolution and Recurrent Layers

Yijun Xiao, Kyunghyun Cho

Document classification tasks were primarily tackled at word level. Recent research that works with character-level inputs shows several benefits over word-level approaches such as…