Injecting Entity Types into Entity-Guided Text Generation
@article{Dong2020InjectingET, title={Injecting Entity Types into Entity-Guided Text Generation}, author={Xiangyu Dong and W. Yu and Chenguang Zhu and Meng Jiang}, journal={ArXiv}, year={2020}, volume={abs/2009.13401} }
Recent successes in deep generative modeling have led to significant advances in natural language generation (NLG). Incorporating entities into neural generation models has demonstrated great improvements by assisting to infer the summary topic and to generate coherent content. In order to enhance the role of entity in NLG, in this paper, we aim to model the entity type in the decoding phase to generate contextual words accurately. We develop a novel NLG model to produce a target sequence (i.e… Expand
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SHOWING 1-10 OF 41 REFERENCES
Entity Commonsense Representation for Neural Abstractive Summarization
- Computer Science
- NAACL-HLT
- 2018
- 22
- PDF
Stick to the Facts: Learning towards a Fidelity-oriented E-Commerce Product Description Generation
- Computer Science
- EMNLP
- 2019
- 8
- PDF
A Knowledge-Enhanced Pretraining Model for Commonsense Story Generation
- Computer Science
- Transactions of the Association for Computational Linguistics
- 2020
- 31
- PDF
Unified Language Model Pre-training for Natural Language Understanding and Generation
- Computer Science
- NeurIPS
- 2019
- 356
- PDF