Biao Zhang

Ship motion prediction of combination forecasting model based on adaptive variable weight

2015

For the problem of large prediction error which is caused by some kind of method in constant weight combination forecasting model predicted result mutate, this paper proposes an adaptive variable weight combination forecasting model. And …

Simplifying Neural Machine Translation with Addition-Subtraction Twin-Gated Recurrent Networks

2018 · arXiv (Cornell University)

In this paper, we propose an additionsubtraction twin-gated recurrent network (ATR) to simplify neural machine translation. The recurrent units of ATR are heavily simplified to have the smallest number of weight matrices among units of …

On Sparsifying Encoder Outputs in Sequence-to-Sequence Models

2021

Sequence-to-sequence models usually transfer all encoder outputs to the decoder for generation. In this work, by contrast, we hypothesize that these encoder outputs can be compressed to shorten the sequence delivered for decoding. We take …

Sparse Attention with Linear Units

2021 · Zurich Open Repository and Archive (University of Zurich)

Recently, it has been argued that encoder-decoder models can be made more interpretable by replacing the softmax function in the attention with its sparse variants. In this work, we introduce a novel, simple method for …

Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documents

2021 · arXiv (Cornell University)

Document-level neural machine translation (DocNMT) achieves coherent translations by incorporating cross-sentence context. However, for most language pairs there's a shortage of parallel documents, although parallel sentences are readily available. In this paper, we study whether …

Revisiting Low-Resource Neural Machine Translation: A Case Study

2019

It has been shown that the performance of neural machine translation (NMT) drops starkly in low-resource conditions, underperforming phrase-based statistical machine translation (PBSMT) and requiring large amounts of auxiliary data to achieve competitive results. In …

Variational Neural Machine Translation

2016

Models of neural machine translation are often from a discriminative family of encoderdecoders that learn a conditional distribution of a target sentence given a source sentence. In this paper, we propose a variational model to …