KB-to-Language Generation
3 papers with code • 1 benchmarks • 1 datasets
Given information from a knowledge base, generate a description of this information in natural language.
Benchmarks
These leaderboards are used to track progress in KB-to-Language Generation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
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Wikipedia Person and Animal Dataset
Most implemented papers
Investigating Pretrained Language Models for Graph-to-Text Generation
UKPLab/plms-graph2text
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EMNLP (NLP4ConvAI) 2021
We show that the PLMs BART and T5 achieve new state-of-the-art results and that task-adaptive pretraining strategies improve their performance even further.
Describing a Knowledge Base
EagleW/Describing_a_Knowledge_Base
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WS 2018
We aim to automatically generate natural language descriptions about an input structured knowledge base (KB).
Stage-wise Fine-tuning for Graph-to-Text Generation
EagleW/Stage-wise-Fine-tuning
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ACL 2021
Graph-to-text generation has benefited from pre-trained language models (PLMs) in achieving better performance than structured graph encoders.
