Yingce Xia

Semi-Supervised Neural Machine Translation via Marginal Distribution Estimation

2019 · IEEE/ACM Transactions on Audio Speech and Language Processing

Neural machine translation (NMT) heavily relies on parallel bilingual corpora for training. Since large-scale, high-quality parallel corpora are usually costly to collect, it is appealing to exploit monolingual corpora to improve NMT. Inspired by the …

RetroGraph: Retrosynthetic Planning with Graph Search

2023 · VBN Forskningsportal (Aalborg Universitet)

The data and checkpoint for "RetroGraph: Retrosynthetic Planning with Graph Search"

Dual Learning for Machine Translation

2016 · arXiv (Cornell University)

While neural machine translation (NMT) is making good progress in the past two years, tens of millions of bilingual sentence pairs are needed for its training. However, human labeling is very costly. To tackle this …

Deliberation Networks: Sequence Generation Beyond One-Pass Decoding

2017 · Neural Information Processing Systems

The encoder-decoder framework has achieved promising progress for many sequence generation tasks, including machine translation, text summarization, dialog system, image captioning, etc. Such a framework adopts an one-pass forward process while decoding and generating a …

Achieving Human Parity on Automatic Chinese to English News Translation

2018 · arXiv (Cornell University)

Machine translation has made rapid advances in recent years. Millions of people are using it today in online translation systems and mobile applications in order to communicate across language barriers. The question naturally arises whether …

Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation

2018 · Neural Information Processing Systems

Neural Machine Translation (NMT) has achieved remarkable progress with the quick evolvement of model structures. In this paper, we propose the concept of layer-wise coordination for NMT, which explicitly coordinates the learning of hidden representations …

BioGPT: generative pre-trained transformer for biomedical text generation and mining

2022 · Briefings in Bioinformatics

Pre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain. Among the two main branches of pre-trained language models in the general language …