Automatic Logical Forms improve fidelity in Table-to-Text generation

Author:

Alonso IñigoORCID,Agirre EnekoORCID

Funder

Eusko Jaurlaritza

Ministerio de Ciencia e Innovación

European Commission

Agencia Estatal de Investigación

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference50 articles.

1. HTLM: Hyper-text pre-training and prompting of language models;Aghajanyan,2022

2. Banarescu, L., Bonial, C., Cai, S., Georgescu, M., Griffitt, K., Hermjakob, U., Knight, K., Koehn, P., Palmer, M., & Schneider, N. (2012). Abstract meaning representation (amr) 1.0 specification. In Parsing on Freebase from Question-Answer Pairs. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. Seattle: ACL (pp. 1533–1544).

3. BLOOM (revision 4ab0472);BigScience Workshop,2022

4. ValueNet: A natural language-to-SQL system that learns from database information;Brunner,2021

5. Meaning and necessity: a study in semantics and modal logic;Carnap,1947

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