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20192025
most citedAMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

39 citations · 40 across the 4 of their papers we have counts for

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cs.CL202139 cited

AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processing

Katikapalli Subramanyam Kalyan, Ajit Rajasekharan, Sivanesan Sangeetha

Transformer-based pretrained language models (T-PTLMs) have achieved great success in almost every NLP task. The evolution of these models started with GPT and BERT. These models a…

cs.CL2021

AMMU : A Survey of Transformer-based Biomedical Pretrained Language Models

Katikapalli Subramanyam Kalyan, Ajit Rajasekharan, Sivanesan Sangeetha

Transformer-based pretrained language models (PLMs) have started a new era in modern natural language processing (NLP). These models combine the power of transformers, transfer lea…

cs.CL2020

Want to Identify, Extract and Normalize Adverse Drug Reactions in Tweets? Use RoBERTa

Katikapalli Subramanyam Kalyan, S. Sangeetha

This paper presents our approach for task 2 and task 3 of Social Media Mining for Health (SMM4H) 2020 shared tasks. In task 2, we have to differentiate adverse drug reaction (ADR)…

cs.CL20201 cited

Medical Concept Normalization in User Generated Texts by Learning Target Concept Embeddings

Katikapalli Subramanyam Kalyan, S. Sangeetha

Medical concept normalization helps in discovering standard concepts in free-form text i.e., maps health-related mentions to standard concepts in a vocabulary. It is much beyond si…

cs.CL2019

SECNLP: A Survey of Embeddings in Clinical Natural Language Processing

Kalyan KS, S Sangeetha

Traditional representations like Bag of words are high dimensional, sparse and ignore the order as well as syntactic and semantic information. Distributed vector representations or…