15 citations · 38 across the 8 of their papers we have counts for
9 papers
SPARTAN: Sparse Hierarchical Memory for Parameter-Efficient Transformers
Ameet Deshpande, Md Arafat Sultan, Anthony Ferritto +3
Fine-tuning pre-trained language models (PLMs) achieves impressive performance on a range of downstream tasks, and their sizes have consequently been getting bigger. Since a differ…
GAAMA 2.0: An Integrated System that Answers Boolean and Extractive Questions
Scott McCarley, Mihaela Bornea, Sara Rosenthal +4
Recent machine reading comprehension datasets include extractive and boolean questions but current approaches do not offer integrated support for answering both question types. We…
VAULT: VAriable Unified Long Text Representation for Machine Reading Comprehension
Haoyang Wen, Anthony Ferritto, Heng Ji +2
Existing models on Machine Reading Comprehension (MRC) require complex model architecture for effectively modeling long texts with paragraph representation and classification, ther…
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…
The TechQA Dataset
Vittorio Castelli, Rishav Chakravarti, Saswati Dana +18
We introduce TechQA, a domain-adaptation question answering dataset for the technical support domain. The TechQA corpus highlights two real-world issues from the automated customer…
Ensembling Strategies for Answering Natural Questions
Anthony Ferritto, Lin Pan, Rishav Chakravarti +4
Many of the top question answering systems today utilize ensembling to improve their performance on tasks such as the Stanford Question Answering Dataset (SQuAD) and Natural Questi…