Web: http://arxiv.org/abs/2209.12577

Sept. 28, 2022, 1:16 a.m. | Tom Sherborne, Mirella Lapata

cs.CL updates on arXiv.org arxiv.org

Localizing a semantic parser to support new languages requires effective
cross-lingual generalization. Recent work has found success with
machine-translation or zero-shot methods although these approaches can struggle
to model how native speakers ask questions. We consider how to effectively
leverage minimal annotated examples in new languages for few-shot cross-lingual
semantic parsing. We introduce a first-order meta-learning algorithm to train a
semantic parser with maximal sample efficiency during cross-lingual transfer.
Our algorithm uses high-resource languages to train the parser and
simultaneously …

arxiv cross-lingual manifold meta meta-learning parsing semantic

More from arxiv.org / cs.CL updates on arXiv.org


@ METRO/MAKRO | Nanterre, France

Data Analyst

@ Netcentric | Barcelona, Spain

Power BI Developer

@ Lendi Group | Sydney, Australia

Staff Data Scientist - Merchant Services (Remote, North America)

@ Shopify | Dallas, TX, United States

Machine Learning / Data Engineer

@ WATI | Vietnam - Remote

F/H Data Manager

@ Bosch Group | Saint-Ouen-sur-Seine, France

[Fixed-term contract until July 2023] Data Quality Controller - Space Industry Luxembourg (m/f/o)

@ LuxSpace Sarl | Betzdorf, Luxembourg

Senior Data Engineer (Azure DataBricks/datalake)

@ SpectraMedix | East Windsor, NJ, United States

Abschlussarbeit im Bereich Data Analytics (w/m/div.)

@ Bosch Group | Rülzheim, Germany

Data Engineer - Marketing

@ Publicis Groupe | London, United Kingdom

Data Engineer (Consulting division)

@ Starschema | Budapest, Hungary

Team Leader, Master Data Management - Support CN, HK & TW

@ Publicis Groupe | Kuala Lumpur, Malaysia