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Found 11 papers, 0 papers with code
Alexa Teacher Model: Pretraining and Distilling Multi-Billion-Parameter Encoders for Natural Language Understanding Systems
We present results from a large-scale experiment on pretraining encoders with non-embedding parameter counts ranging from 700M to 9. 3B, their subsequent distillation into smaller models ranging from 17M-170M parameters, and their application to the Natural Language Understanding (NLU) component of a virtual assistant system.
Cross-Lingual Natural Language Inference
intent-classification
+5
Continuous Model Improvement for Language Understanding with Machine Translation
Scaling conversational personal assistants to a multitude of languages puts high demands on collecting and labelling data, a setting in which cross-lingual learning techniques can help to reconcile the need for well-performing Natural Language Understanding (NLU) with a desideratum to support many languages without incurring unacceptable cost.
SemEval-2018 Task 9: Hypernym Discovery
This paper describes the SemEval 2018 Shared Task on Hypernym Discovery.
Neural Sequence Learning Models for Word Sense Disambiguation
Word Sense Disambiguation models exist in many flavors.
Ranked #19 on
Word Sense Disambiguation
on Supervised:
SupWSD: A Flexible Toolkit for Supervised Word Sense Disambiguation
In this demonstration we present SupWSD, a Java API for supervised Word Sense Disambiguation (WSD).
Sew-Embed at SemEval-2017 Task 2: Language-Independent Concept Representations from a Semantically Enriched Wikipedia
This paper describes Sew-Embed, our language-independent approach to multilingual and cross-lingual semantic word similarity as part of the SemEval-2017 Task 2.
EuroSense: Automatic Harvesting of Multilingual Sense Annotations from Parallel Text
Parallel corpora are widely used in a variety of Natural Language Processing tasks, from Machine Translation to cross-lingual Word Sense Disambiguation, where parallel sentences can be exploited to automatically generate high-quality sense annotations on a large scale.
A Large-Scale Multilingual Disambiguation of Glosses
Linking concepts and named entities to knowledge bases has become a crucial Natural Language Understanding task.
Large-Scale Information Extraction from Textual Definitions through Deep Syntactic and Semantic Analysis
The output of DefIE is a high-quality knowledge base consisting of several million automatically acquired semantic relations.
