464 citations · 628 across the 21 of their papers we have counts for
4 papers · 1 filter
Training Compact Models for Low Resource Entity Tagging using Pre-trained Language Models
Peter Izsak, Shira Guskin, Moshe Wasserblat
Training models on low-resource named entity recognition tasks has been shown to be a challenge, especially in industrial applications where deploying updated models is a continuou…
Q8BERT: Quantized 8Bit BERT
Ofir Zafrir, Guy Boudoukh, Peter Izsak +1
Recently, pre-trained Transformer based language models such as BERT and GPT, have shown great improvement in many Natural Language Processing (NLP) tasks. However, these models co…
ABSApp: A Portable Weakly-Supervised Aspect-Based Sentiment Extraction System
Oren Pereg, Daniel Korat, Moshe Wasserblat +2
We present ABSApp, a portable system for weakly-supervised aspect-based sentiment extraction. The system is interpretable and user friendly and does not require labeled training da…
Multi-Context Term Embeddings: the Use Case of Corpus-based Term Set Expansion
Jonathan Mamou, Oren Pereg, Moshe Wasserblat +1
In this paper, we present a novel algorithm that combines multi-context term embeddings using a neural classifier and we test this approach on the use case of corpus-based term set…