10 citations · 12 across the 4 of their papers we have counts for
6 papers · 1 filter
Domain Adaptive Pretraining for Multilingual Acronym Extraction
Usama Yaseen, Stefan Langer
This paper presents our findings from participating in the multilingual acronym extraction shared task SDU@AAAI-22. The task consists of acronym extraction from documents in 6 lang…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
Data Augmentation for Low-Resource Named Entity Recognition Using Backtranslation
Usama Yaseen, Stefan Langer
The state of art natural language processing systems relies on sizable training datasets to achieve high performance. Lack of such datasets in the specialized low resource domains…
Neural Text Classification and Stacked Heterogeneous Embeddings for Named Entity Recognition in SMM4H 2021
Usama Yaseen, Stefan Langer
This paper presents our findings from participating in the SMM4H Shared Task 2021. We addressed Named Entity Recognition (NER) and Text Classification. To address NER we explored B…
Linguistically Informed Relation Extraction and Neural Architectures for Nested Named Entity Recognition in BioNLP-OST 2019
Usama Yaseen, Pankaj Gupta, Hinrich Schütze
Named Entity Recognition (NER) and Relation Extraction (RE) are essential tools in distilling knowledge from biomedical literature. This paper presents our findings from participat…
Neural Architectures for Fine-Grained Propaganda Detection in News
Pankaj Gupta, Khushbu Saxena, Usama Yaseen +2
This paper describes our system (MIC-CIS) details and results of participation in the fine-grained propaganda detection shared task 2019. To address the tasks of sentence (SLC) and…