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Found 9 papers, 5 papers with code
Improving Non-Autoregressive Neural Machine Translation via Modeling Localness
Non-autoregressive translation (NAT) models, which eliminate the sequential dependencies within the target sentence, have achieved remarkable inference speed, but suffer from inferior translation quality.
Towards Higher Pareto Frontier in Multilingual Machine Translation
Multilingual neural machine translation has witnessed remarkable progress in recent years.
Unifying the Convergences in Multilingual Neural Machine Translation
In this paper, we propose a novel training strategy named LSSD (Language-Specific Self-Distillation), which can alleviate the convergence inconsistency and help MNMT models achieve the best performance on each language pair simultaneously.
Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarization
First, we present a Dialogue Discourse-Dware Meeting Summarizer (DDAMS) to explicitly model the interaction between utterances in a meeting by modeling different discourse relations.
How Does Selective Mechanism Improve Self-Attention Networks?
Self-attention networks (SANs) with selective mechanism has produced substantial improvements in various NLP tasks by concentrating on a subset of input words.
Learning to Refine Source Representations for Neural Machine Translation
Neural machine translation (NMT) models generally adopt an encoder-decoder architecture for modeling the entire translation process.
Adaptive Multi-pass Decoder for Neural Machine Translation
Although end-to-end neural machine translation (NMT) has achieved remarkable progress in the recent years, the idea of adopting multi-pass decoding mechanism into conventional NMT is not well explored.
A Planning based Framework for Essay Generation
Generating an article automatically with computer program is a challenging task in artificial intelligence and natural language processing.
