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Graph-to-Sequence
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Mapping an input graph to a sequence of vectors.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
EzSQL: An SQL intermediate representation for improving SQL-to-text Generation
Ontology-Free General-Domain Knowledge Graph-to-Text Generation Dataset Synthesis using Large Language Model
Ask Questions with Double Hints: Visual Question Generation with Answer-awareness and Region-reference
UAlign: Pushing the Limit of Template-free Retrosynthesis Prediction with Unsupervised SMILES Alignment
Predicting Parking Lot Availability by Graph-to-Sequence Model: A Case Study with SmartSantander
Topic-Guided Abstractive Multi-Document Summarization
Permutation invariant graph-to-sequence model for template-free retrosynthesis and reaction prediction
Proving Equivalence Between Complex Expressions Using Graph-to-Sequence Neural Models
GraphPB: Graphical Representations of Prosody Boundary in Speech Synthesis
Graph-to-Sequence Neural Machine Translation
Sparse Graph to Sequence Learning for Vision Conditioned Long Textual Sequence Generation
GPT-too: A language-model-first approach for AMR-to-text generation
ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
Learning to Encode Evolutionary Knowledge for Automatic Commenting Long Novels
GraphTTS: graph-to-sequence modelling in neural text-to-speech
Equivalence of Dataflow Graphs via Rewrite Rules Using a Graph-to-Sequence Neural Model
Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs
Graph Transformer for Graph-to-Sequence Learning
Natural Question Generation with Reinforcement Learning Based Graph-to-Sequence Model
Enhancing AMR-to-Text Generation with Dual Graph Representations
DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums
Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning
Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation
Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence Model
STG2Seq: Spatial-temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting
Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation
Structural Neural Encoders for AMR-to-text Generation
Fleet Prognosis with Physics-informed Recurrent Neural Networks
Deep Graph Convolutional Encoders for Structured Data to Text Generation
SQL-to-Text Generation with Graph-to-Sequence Model
Exploiting Rich Syntactic Information for Semantic Parsing with Graph-to-Sequence Model
Graph-to-Sequence Learning using Gated Graph Neural Networks
A Graph-to-Sequence Model for AMR-to-Text Generation
Graph2Seq: Graph to Sequence Learning with Attention-based Neural Networks
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation
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