32 citations · 33 across the 3 of their papers we have counts for
3 papers
A Systematic Study of Knowledge Distillation for Natural Language Generation with Pseudo-Target Training
Nitay Calderon, Subhabrata Mukherjee, Roi Reichart +1
Modern Natural Language Generation (NLG) models come with massive computational and storage requirements. In this work, we study the potential of compressing them, which is crucial…
MeeQA: Natural Questions in Meeting Transcripts
Reut Apel, Tom Braude, Amir Kantor +1
We present MeeQA, a dataset for natural-language question answering over meeting transcripts. It includes real questions asked during meetings by its participants. The dataset cont…
Not Enough Data? Deep Learning to the Rescue!
Ateret Anaby-Tavor, Boaz Carmeli, Esther Goldbraich +5
Based on recent advances in natural language modeling and those in text generation capabilities, we propose a novel data augmentation method for text classification tasks. We use a…