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Found 7 papers, 2 papers with code
Methods for Numeracy-Preserving Word Embeddings
We propose a new methodology to assign and learn embeddings for numbers.
Learning Task Sampling Policy for Multitask Learning
It has been shown that training multi-task models with auxiliary tasks can improve the target task quality through cross-task transfer.
Number Entity Recognition
Numbers are essential components of text, like any other word tokens, from which natural language processing (NLP) models are built and deployed.
How do lexical semantics affect translation? An empirical study
Neural machine translation (NMT) systems aim to map text from one language into another.
Syntax-Infused Transformer and BERT models for Machine Translation and Natural Language Understanding
Attention-based models have shown significant improvement over traditional algorithms in several NLP tasks.
Learning Compressed Sentence Representations for On-Device Text Processing
Vector representations of sentences, trained on massive text corpora, are widely used as generic sentence embeddings across a variety of NLP problems.
How much is my car worth? A methodology for predicting used cars prices using Random Forest
Cars are being sold more than ever.
