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Found 10 papers, 2 papers with code
Improving Non-autoregressive Machine Translation with Error Exposure and Consistency Regularization
Being one of the IR-NAT (Iterative-refinemennt-based NAT) frameworks, the Conditional Masked Language Model (CMLM) adopts the mask-predict paradigm to re-predict the masked low-confidence tokens.
Multi-grained Evidence Inference for Multi-choice Reading Comprehension
Multi-choice Machine Reading Comprehension (MRC) is a major and challenging task for machines to answer questions according to provided options.
To Understand Representation of Layer-aware Sequence Encoders as Multi-order-graph
We also propose a revisited multigraph called Multi-order-Graph (MoG) based on our explanation to model the graph structures in the SAN-based model as subgraphs in MoG and convert the encoding of SAN-based model to the generation of MoG.
SG-Net: Syntax Guided Transformer for Language Representation
In detail, for self-attention network (SAN) sponsored Transformer-based encoder, we introduce syntactic dependency of interest (SDOI) design into the SAN to form an SDOI-SAN with syntax-guided self-attention.
Graph-to-Sequence Neural Machine Translation
In the light of the current NMT models more or less capture graph information among the sequence in a latent way, we present a graph-to-sequence model facilitating explicit graph information capturing.
Capsule-Transformer for Neural Machine Translation
In this paper, we thus propose the capsule-Transformer, which extends the linear transformation into a more general capsule routing algorithm by taking SAN as a special case of capsule network.
Syntax-aware Data Augmentation for Neural Machine Translation
Data augmentation is an effective performance enhancement in neural machine translation (NMT) by generating additional bilingual data.
Attention Is All You Need for Chinese Word Segmentation
Taking greedy decoding algorithm as it should be, this work focuses on further strengthening the model itself for Chinese word segmentation (CWS), which results in an even more fast and more accurate CWS model.
SG-Net: Syntax-Guided Machine Reading Comprehension
In detail, for self-attention network (SAN) sponsored Transformer-based encoder, we introduce syntactic dependency of interest (SDOI) design into the SAN to form an SDOI-SAN with syntax-guided self-attention.
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Fast Neural Chinese Word Segmentation for Long Sentences
Rapidly developed neural models have achieved competitive performance in Chinese word segmentation (CWS) as their traditional counterparts.
