21 citations · 25 across the 8 of their papers we have counts for
3 papers · 1 filter
How to Select One Among All? An Extensive Empirical Study Towards the Robustness of Knowledge Distillation in Natural Language Understanding
Tianda Li, Ahmad Rashid, Aref Jafari +3
Knowledge Distillation (KD) is a model compression algorithm that helps transfer the knowledge of a large neural network into a smaller one. Even though KD has shown promise on a w…
Context-aware Adversarial Training for Name Regularity Bias in Named Entity Recognition
Abbas Ghaddar, Philippe Langlais, Ahmad Rashid +1
In this work, we examine the ability of NER models to use contextual information when predicting the type of an ambiguous entity. We introduce NRB, a new testbed carefully designed…
MATE-KD: Masked Adversarial TExt, a Companion to Knowledge Distillation
Ahmad Rashid, Vasileios Lioutas, Mehdi Rezagholizadeh
The advent of large pre-trained language models has given rise to rapid progress in the field of Natural Language Processing (NLP). While the performance of these models on standar…