2 citations · 4 across the 4 of their papers we have counts for
6 papers
Parameter and Data Efficient Continual Pre-training for Robustness to Dialectal Variance in Arabic
Soumajyoti Sarkar, Kaixiang Lin, Sailik Sengupta +3
The use of multilingual language models for tasks in low and high-resource languages has been a success story in deep learning. In recent times, Arabic has been receiving widesprea…
Label Semantic Aware Pre-training for Few-shot Text Classification
Aaron Mueller, Jason Krone, Salvatore Romeo +4
In text classification tasks, useful information is encoded in the label names. Label semantic aware systems have leveraged this information for improved text classification perfor…
Nearest Neighbour Few-Shot Learning for Cross-lingual Classification
M Saiful Bari, Batool Haider, Saab Mansour
Even though large pre-trained multilingual models (e.g. mBERT, XLM-R) have led to significant performance gains on a wide range of cross-lingual NLP tasks, success on many downstre…
Soft Layer Selection with Meta-Learning for Zero-Shot Cross-Lingual Transfer
Weijia Xu, Batool Haider, Jason Krone +1
Multilingual pre-trained contextual embedding models (Devlin et al., 2019) have achieved impressive performance on zero-shot cross-lingual transfer tasks. Finding the most effectiv…
On the Robustness of Intent Classification and Slot Labeling in Goal-oriented Dialog Systems to Real-world Noise
Sailik Sengupta, Jason Krone, Saab Mansour
Intent Classification (IC) and Slot Labeling (SL) models, which form the basis of dialogue systems, often encounter noisy data in real-word environments. In this work, we investiga…
End-to-End Slot Alignment and Recognition for Cross-Lingual NLU
Weijia Xu, Batool Haider, Saab Mansour
Natural language understanding (NLU) in the context of goal-oriented dialog systems typically includes intent classification and slot labeling tasks. Existing methods to expand an…