5 citations · 14 across the 14 of their papers we have counts for
14 papers
PropaInsight: Toward Deeper Understanding of Propaganda in Terms of Techniques, Appeals, and Intent
Jiateng Liu, Lin Ai, Zizhou Liu +6
Propaganda plays a critical role in shaping public opinion and fueling disinformation. While existing research primarily focuses on identifying propaganda techniques, it lacks the…
Fact Checking Beyond Training Set
Payam Karisani, Heng Ji
Evaluating the veracity of everyday claims is time consuming and in some cases requires domain expertise. We empirically demonstrate that the commonly used fact checking pipeline,…
Masked LoGoNet: Fast and Accurate 3D Image Analysis for Medical Domain
Amin Karimi Monsefi, Payam Karisani, Mengxi Zhou +5
Standard modern machine-learning-based imaging methods have faced challenges in medical applications due to the high cost of dataset construction and, thereby, the limited labeled…
Named Entity Recognition Under Domain Shift via Metric Learning for Life Sciences
Hongyi Liu, Qingyun Wang, Payam Karisani +1
Named entity recognition is a key component of Information Extraction (IE), particularly in scientific domains such as biomedicine and chemistry, where large language models (LLMs)…
Neural Networks Against (and For) Self-Training: Classification with Small Labeled and Large Unlabeled Sets
Payam Karisani
We propose a semi-supervised text classifier based on self-training using one positive and one negative property of neural networks. One of the weaknesses of self-training is the s…
Ericson: An Interactive Open-Domain Conversational Search Agent
Zihao Wang, Ali Ahmadvand, Jason Choi +2
Open-domain conversational search (ODCS) aims to provide valuable, up-to-date information, while maintaining natural conversations to help users refine and ultimately answer inform…
Detecting Elevated Air Pollution Levels by Monitoring Web Search Queries: Deep Learning-Based Time Series Forecasting
Chen Lin, Safoora Yousefi, Elvis Kahoro +4
Real-time air pollution monitoring is a valuable tool for public health and environmental surveillance. In recent years, there has been a dramatic increase in air pollution forecas…
Multiple-Source Domain Adaptation via Coordinated Domain Encoders and Paired Classifiers
Payam Karisani
We present a novel multiple-source unsupervised model for text classification under domain shift. Our model exploits the update rates in document representations to dynamically int…
Multi-View Active Learning for Short Text Classification in User-Generated Data
Payam Karisani, Negin Karisani, Li Xiong
Mining user-generated data often suffers from the lack of enough labeled data, short document lengths, and the informal user language. In this paper, we propose a novel active lear…
Semi-Supervised Text Classification via Self-Pretraining
Payam Karisani, Negin Karisani
We present a neural semi-supervised learning model termed Self-Pretraining. Our model is inspired by the classic self-training algorithm. However, as opposed to self-training, Self…
View Distillation with Unlabeled Data for Extracting Adverse Drug Effects from User-Generated Data
Payam Karisani, Jinho D. Choi, Li Xiong
We present an algorithm based on multi-layer transformers for identifying Adverse Drug Reactions (ADR) in social media data. Our model relies on the properties of the problem and t…
Domain-Guided Task Decomposition with Self-Training for Detecting Personal Events in Social Media
Payam Karisani, Joyce C. Ho, Eugene Agichtein
Mining social media content for tasks such as detecting personal experiences or events, suffer from lexical sparsity, insufficient training data, and inventive lexicons. To reduce…
Mining Coronavirus (COVID-19) Posts in Social Media
Negin Karisani, Payam Karisani
World Health Organization (WHO) characterized the novel coronavirus (COVID-19) as a global pandemic on March 11th, 2020. Before this and in late January, more specifically on Janua…
Did You Really Just Have a Heart Attack? Towards Robust Detection of Personal Health Mentions in Social Media
Payam Karisani, Eugene Agichtein
Millions of users share their experiences on social media sites, such as Twitter, which in turn generate valuable data for public health monitoring, digital epidemiology, and other…