← Back to papers
2019 CONLL CoNLL 2019

Hitachi at MRP 2019: Unified Encoder-to-Biaffine Network for Cross-Framework Meaning Representation Parsing

🧭 Keyword Pioneer — biaffine network
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Yuta Koreeda , Gaku Morio , Terufumi Morishita , Hiroaki Ozaki , Kohsuke Yanai

Topics

Machine Learning > Core Methods > Representation Learning Machine Learning > Learning Types > Multi-Task Learning

Keywords

multi-task learning semantic parsing meaning representation graph parsing biaffine network
Download PDF

Related papers

Deconstructing Supertagging into Multi-Task Sequence Prediction 2019
Large-Scale Representation Learning from Visually Grounded Untranscribed Speech 2019
Say Anything: Automatic Semantic Infelicity Detection in L2 English Indefinite Pronouns 2019
Federated Learning of N-Gram Language Models 2019
Learning Conceptual Spaces with Disentangled Facets 2019