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Graph-to-Sequence

9 papers with code · Natural Language Processing

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A Graph-to-Sequence Model for AMR-to-Text Generation

ACL 2018 freesunshine0316/neural-graph-to-seq-mp

The problem of AMR-to-text generation is to recover a text representing the same meaning as an input AMR graph.

 SOTA for Graph-to-Sequence on LDC2015E86: (using extra training data)

GRAPH-TO-SEQUENCE TEXT GENERATION

Neural AMR: Sequence-to-Sequence Models for Parsing and Generation

ACL 2017 freesunshine0316/neural-graph-to-seq-mp

Sequence-to-sequence models have shown strong performance across a broad range of applications.

AMR PARSING GRAPH-TO-SEQUENCE

Graph2Seq: Graph to Sequence Learning with Attention-based Neural Networks

ICLR 2019 IBM/Graph2Seq

Our method first generates the node and graph embeddings using an improved graph-based neural network with a novel aggregation strategy to incorporate edge direction information in the node embeddings.

GRAPH-TO-SEQUENCE SQL-TO-TEXT TEXT GENERATION

Deep Graph Convolutional Encoders for Structured Data to Text Generation

WS 2018 diegma/graph-2-text

Most previous work on neural text generation from graph-structured data relies on standard sequence-to-sequence methods.

DATA-TO-TEXT GENERATION GRAPH-TO-SEQUENCE

Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation

NAACL 2019 AmitMY/chimera

We propose to split the generation process into a symbolic text-planning stage that is faithful to the input, followed by a neural generation stage that focuses only on realization.

DATA-TO-TEXT GENERATION GRAPH-TO-SEQUENCE

SQL-to-Text Generation with Graph-to-Sequence Model

EMNLP 2018 IBM/SQL-to-Text

Previous work approaches the SQL-to-text generation task using vanilla Seq2Seq models, which may not fully capture the inherent graph-structured information in SQL query.

GRAPH-TO-SEQUENCE SQL-TO-TEXT TEXT GENERATION

Structural Neural Encoders for AMR-to-text Generation

NAACL 2019 mdtux89/OpenNMT-py-AMR-to-text

AMR-to-text generation is a problem recently introduced to the NLP community, in which the goal is to generate sentences from Abstract Meaning Representation (AMR) graphs.

GRAPH-TO-SEQUENCE TEXT GENERATION

Enhancing AMR-to-Text Generation with Dual Graph Representations

1 Sep 2019UKPLab/emnlp2019-dualgraph

Generating text from graph-based data, such as Abstract Meaning Representation (AMR), is a challenging task due to the inherent difficulty in how to properly encode the structure of a graph with labeled edges.

GRAPH-TO-SEQUENCE TEXT GENERATION