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KG-to-Text Generation
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Knowledge-graph-to-text (KG-to-text) generation aims to generate high-quality texts which are consistent with input graphs.
Description from: JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Can Knowledge Graphs Simplify Text?
Generating Faithful Text From a Knowledge Graph with Noisy Reference Text
Using Large Language Models for Zero-Shot Natural Language Generation from Knowledge Graphs
Knowledge Graph for NLG in the context of conversational agents
Syntax Controlled Knowledge Graph-to-Text Generation with Order and Semantic Consistency
GAP: A Graph-aware Language Model Framework for Knowledge Graph-to-Text Generation
EventNarrative: A large-scale Event-centric Dataset for Knowledge Graph-to-Text Generation
WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset
JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs
Few-shot Knowledge Graph-to-Text Generation with Pretrained Language Models
How to Train Your Agent to Read and Write
KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation
Investigating Pretrained Language Models for Graph-to-Text Generation
Modeling Graph Structure via Relative Position for Text Generation from Knowledge Graphs
ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
Toward Subgraph-Guided Knowledge Graph Question Generation with Graph Neural Networks
Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs
Text Generation from Knowledge Graphs with Graph Transformers
Deep Graph Convolutional Encoders for Structured Data to Text Generation
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