16 citations · 17 across the 9 of their papers we have counts for
13 papers
B-CARE: Blind Classwise Assessment of Relative Evidence for Stance Error Ranking
Meysam Sabbaghan, Doina Caragea
Stance classifiers make errors that can be costly to identify under limited human-review budgets. Prioritizing potentially incorrect predictions remains challenging, particularly a…
Conversational AI for Perceived Cognitive Decline Screening in Older Adults
Nikita Gautam, Moana Sargent, Kaitlyn Sievers +4
Early detection of cognitive decline in older adults remains challenging due to the resource demands of standard neuropsychological assessments. Chatbot-based Intelligent Cognitive…
Multi-Agent Reasoning with Adaptive Worker Allocation for Stance Detection
Meysam Sabbaghan, Arman Zareian Jahromi, Doina Caragea
Stance detection requires identifying an author's position toward a target, often from short-form texts where stance is implicit, indirect, or rhetorically framed. Although large l…
LLM-guided Semi-Supervised Approaches for Social Media Crisis Data Classification
Jacob Ativo, Bharaneeshwar Balasubramaniyam, Anh Tran +4
Semi-supervised learning approaches have been investigated as a means to enhance the analysis of social media data in disaster management contexts. In this work, we present the fir…
MSGL-Transformer: A Multi-Scale Global-Local Transformer for Rodent Social Behavior Recognition
Muhammad Imran Sharif, Doina Caragea
Recognition of rodent behavior is important for understanding neural and behavioral mechanisms. Traditional manual scoring is time-consuming and prone to human error. We propose MS…
Practical Insights into Semi-Supervised Object Detection Approaches
Chaoxin Wang, Bharaneeshwar Balasubramaniyam, Anurag Sangem +2
Learning in data-scarce settings has recently gained significant attention in the research community. Semi-supervised object detection(SSOD) aims to improve detection performance b…
The Shifting Landscape of Vaccine Discourse: Insights From a Decade of Pre- to Post-COVID-19 Vaccine Posts on Social Media
Nikesh Gyawali, Doina Caragea, Cornelia Caragea +1
In this work, we study English-language vaccine discourse in social media posts, specifically posts on X (formerly Twitter), in seven years before the COVID-19 outbreak (2013 to 20…
Evaluating Large Language Models for Stance Detection on Financial Targets from SEC Filing Reports and Earnings Call Transcripts
Nikesh Gyawali, Doina Caragea, Alex Vasenkov +1
Financial narratives from U.S. Securities and Exchange Commission (SEC) filing reports and quarterly earnings call transcripts (ECTs) are very important for investors, auditors, an…
A MISMATCHED Benchmark for Scientific Natural Language Inference
Firoz Shaik, Mobashir Sadat, Nikita Gautam +2
Scientific Natural Language Inference (NLI) is the task of predicting the semantic relation between a pair of sentences extracted from research articles. Existing datasets for this…
CrisisMatch: Semi-Supervised Few-Shot Learning for Fine-Grained Disaster Tweet Classification
Henry Peng Zou, Yue Zhou, Cornelia Caragea +1
The shared real-time information about natural disasters on social media platforms like Twitter and Facebook plays a critical role in informing volunteers, emergency managers, and…
Identification of Fine-Grained Location Mentions in Crisis Tweets
Sarthak Khanal, Maria Traskowsky, Doina Caragea
Identification of fine-grained location mentions in crisis tweets is central in transforming situational awareness information extracted from social media into actionable informati…
On Identifying Hashtags in Disaster Twitter Data
Jishnu Ray Chowdhury, Cornelia Caragea, Doina Caragea
Tweet hashtags have the potential to improve the search for information during disaster events. However, there is a large number of disaster-related tweets that do not have any use…
Localizing and Quantifying Damage in Social Media Images
Xukun Li, Huaiyu Zhang, Doina Caragea +1
Traditional post-disaster assessment of damage heavily relies on expensive GIS data, especially remote sensing image data. In recent years, social media has become a rich source of…