148 citations · 781 across the 44 of their papers we have counts for
9 papers · 2 filters
Multilingual Transfer Learning for QA Using Translation as Data Augmentation
Mihaela Bornea, Lin Pan, Sara Rosenthal +2
Prior work on multilingual question answering has mostly focused on using large multilingual pre-trained language models (LM) to perform zero-shot language-wise learning: train a Q…
End-to-End QA on COVID-19: Domain Adaptation with Synthetic Training
Revanth Gangi Reddy, Bhavani Iyer, Md Arafat Sultan +5
End-to-end question answering (QA) requires both information retrieval (IR) over a large document collection and machine reading comprehension (MRC) on the retrieved passages. Rece…
Pushing the Limits of AMR Parsing with Self-Learning
Young-Suk Lee, Ramon Fernandez Astudillo, Tahira Naseem +3
Abstract Meaning Representation (AMR) parsing has experienced a notable growth in performance in the last two years, due both to the impact of transfer learning and the development…
Transition-based Parsing with Stack-Transformers
Ramon Fernandez Astudillo, Miguel Ballesteros, Tahira Naseem +2
Modeling the parser state is key to good performance in transition-based parsing. Recurrent Neural Networks considerably improved the performance of transition-based systems by mod…
Cross-Lingual Relation Extraction with Transformers
Jian Ni, Taesun Moon, Parul Awasthy +1
Relation extraction (RE) is one of the most important tasks in information extraction, as it provides essential information for many NLP applications. In this paper, we propose a c…
Multi-Stage Pre-training for Low-Resource Domain Adaptation
Rong Zhang, Revanth Gangi Reddy, Md Arafat Sultan +7
Transfer learning techniques are particularly useful in NLP tasks where a sizable amount of high-quality annotated data is difficult to obtain. Current approaches directly adapt a…