221 citations · 523 across the 43 of their papers we have counts for
16 papers · 1 filter
SimpleStyle: An Adaptable Style Transfer Approach
Elron Bandel, Yoav Katz, Noam Slonim +1
Attribute-controlled text rewriting, also known as text style-transfer, has a crucial role in regulating attributes and biases of textual training data and a machine generated text…
ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning
Shachar Don-Yehiya, Elad Venezian, Colin Raffel +3
We propose a new paradigm to continually evolve pretrained models, denoted ColD Fusion. It provides the benefits of multitask learning but leverages distributed computation with li…
Where to start? Analyzing the potential value of intermediate models
Leshem Choshen, Elad Venezian, Shachar Don-Yehia +2
Previous studies observed that finetuned models may be better base models than the vanilla pretrained model. Such a model, finetuned on some source dataset, may provide a better st…
nBIIG: A Neural BI Insights Generation System for Table Reporting
Yotam Perlitz, Dafna Sheinwald, Noam Slonim +1
We present nBIIG, a neural Business Intelligence (BI) Insights Generation system. Given a table, our system applies various analyses to create corresponding RDF representations, an…
Zero-Shot Text Classification with Self-Training
Ariel Gera, Alon Halfon, Eyal Shnarch +3
Recent advances in large pretrained language models have increased attention to zero-shot text classification. In particular, models finetuned on natural language inference dataset…
Efficient Methods for Natural Language Processing: A Survey
Marcos Treviso, Ji-Ung Lee, Tianchu Ji +19
Recent work in natural language processing (NLP) has yielded appealing results from scaling model parameters and training data; however, using only scale to improve performance mea…