32 citations · 120 across the 11 of their papers we have counts for
11 papers
Object-Aware Cropping for Self-Supervised Learning
Shlok Mishra, Anshul Shah, Ankan Bansal +5
A core component of the recent success of self-supervised learning is cropping data augmentation, which selects sub-regions of an image to be used as positive views in the self-sup…
Membership Inference Attack Susceptibility of Clinical Language Models
Abhyuday Jagannatha, Bhanu Pratap Singh Rawat, Hong Yu
Deep Neural Network (DNN) models have been shown to have high empirical privacy leakages. Clinical language models (CLMs) trained on clinical data have been used to improve perform…
Federated Intrusion Detection for IoT with Heterogeneous Cohort Privacy
Ajesh Koyatan Chathoth, Abhyuday Jagannatha, Stephen Lee
Internet of Things (IoT) devices are becoming increasingly popular and are influencing many application domains such as healthcare and transportation. These devices are used for re…
Calibrating Structured Output Predictors for Natural Language Processing
Abhyuday Jagannatha, Hong Yu
We address the problem of calibrating prediction confidence for output entities of interest in natural language processing (NLP) applications. It is important that NLP applications…
Towards Automatic Generation of Questions from Long Answers
Shlok Kumar Mishra, Pranav Goel, Abhishek Sharma +3
Automatic question generation (AQG) has broad applicability in domains such as tutoring systems, conversational agents, healthcare literacy, and information retrieval. Existing eff…
Continual Domain-Tuning for Pretrained Language Models
Subendhu Rongali, Abhyuday Jagannatha, Bhanu Pratap Singh Rawat +1
Pre-trained language models (LM) such as BERT, DistilBERT, and RoBERTa can be tuned for different domains (domain-tuning) by continuing the pre-training phase on a new target domai…
Active Learning for New Domains in Natural Language Understanding
Stanislav Peshterliev, John Kearney, Abhyuday Jagannatha +2
We explore active learning (AL) for improving the accuracy of new domains in a natural language understanding (NLU) system. We propose an algorithm called Majority-CRF that uses an…
Ranking medical jargon in electronic health record notes by adapted distant supervision
Jinying Chen, Abhyuday N. Jagannatha, Samah J. Jarad +1
Objective: Allowing patients to access their own electronic health record (EHR) notes through online patient portals has the potential to improve patient-centered care. However, me…
Structured prediction models for RNN based sequence labeling in clinical text
Abhyuday Jagannatha, Hong Yu
Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application…
Bidirectional Recurrent Neural Networks for Medical Event Detection in Electronic Health Records
Abhyuday Jagannatha, Hong Yu
Sequence labeling for extraction of medical events and their attributes from unstructured text in Electronic Health Record (EHR) notes is a key step towards semantic understanding…
Learning for Biomedical Information Extraction: Methodological Review of Recent Advances
Feifan Liu, Jinying Chen, Abhyuday Jagannatha +1
Biomedical information extraction (BioIE) is important to many applications, including clinical decision support, integrative biology, and pharmacovigilance, and therefore it has b…