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20182021
most citedGraph Transformer for Graph-to-Sequence Learning

38 citations · 97 across the 6 of their papers we have counts for

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12 papers · 1 filter

cs.CL202116 cited

Neural Machine Translation with Monolingual Translation Memory

Deng Cai, Yan Wang, Huayang Li +2

Prior work has proved that Translation memory (TM) can boost the performance of Neural Machine Translation (NMT). In contrast to existing work that uses bilingual corpus as TM and…

cs.CL2020

Dialogue Response Selection with Hierarchical Curriculum Learning

Yixuan Su, Deng Cai, Qingyu Zhou +6

We study the learning of a matching model for dialogue response selection. Motivated by the recent finding that models trained with random negative samples are not ideal in real-wo…

cs.CL202010 cited

AMR Parsing via Graph-Sequence Iterative Inference

Deng Cai, Wai Lam

We propose a new end-to-end model that treats AMR parsing as a series of dual decisions on the input sequence and the incrementally constructed graph. At each time step, our model…

cs.CL20206 cited

Prototype-to-Style: Dialogue Generation with Style-Aware Editing on Retrieval Memory

Yixuan Su, Yan Wang, Simon Baker +4

The ability of a dialog system to express prespecified language style during conversations has a direct, positive impact on its usability and on user satisfaction. We introduce a n…

cs.CL201938 cited

Graph Transformer for Graph-to-Sequence Learning

Deng Cai, Wai Lam

The dominant graph-to-sequence transduction models employ graph neural networks for graph representation learning, where the structural information is reflected by the receptive fi…

cs.CL2019

Core Semantic First: A Top-down Approach for AMR Parsing

Deng Cai, Wai Lam

We introduce a novel scheme for parsing a piece of text into its Abstract Meaning Representation (AMR): Graph Spanning based Parsing (GSP). One novel characteristic of GSP is that…