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Anirban Laha

Biographic Data

ID6536305
NAMEAnirban Laha
GIVEN NAMESAnirban
FAMILY NAMELaha
SIGNATURELAHA A
AFFILIATIONSMila, Université de Montréal.
VERIFIEDNo
TOTAL WORKS1
TOTAL CITATIONS0
WORKS AS AUTHOR1
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2019
LATEST PUBLICATION YEAR2019
H-INDEX0
  • Scalable Micro-planned Generation of Discourse from Structured Data

    Open Access•Anirban Laha, Parag Jain et al.•ARTICLE•Computational Linguistics•2019•References: 2

    We present a framework for generating natural language description from structured data such as tables; the problem comes under the category of data-to-text natural language generation (NLG). Modern data-to-text NLG systems typically use end-to-end statistical and neural architectures that learn from a limited amount of task-specific labeled data, and therefore exhibit limited scalability, domain-adaptability, and interpretability. Unlike these s…

No prominent works on this page.

  • Scalable Micro-planned Generation of Discourse from Structured Data

    Open Access•Anirban Laha, Parag Jain et al.•ARTICLE•Computational Linguistics•2019•References: 2

    We present a framework for generating natural language description from structured data such as tables; the problem comes under the category of data-to-text natural language generation (NLG). Modern data-to-text NLG systems typically use end-to-end statistical and neural architectures that learn from a limited amount of task-specific labeled data, and therefore exhibit limited scalability, domain-adaptability, and interpretability. Unlike these s…

Artificial Intelligence (1 work) · Computer Science (1 work) · Database (1 work) · Fluency (1 work) · Interpretability (1 work) · Multimodal Machine Learning Applications (1 work) · Natural language (1 work) · Natural Language Generation (1 work) · Natural language processing (1 work) · Natural Language Processing Techniques (1 work)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae