39 citations · 64 across the 16 of their papers we have counts for
16 papers
Beyond Aggregate Scores: Behavioral Correctness Assumptions for Assessing Reference-Based Automatic Evaluation Methods
Maria Mahbub, Ashley Rice, Michael R. Munroe +2
Automated reference-based evaluation methods play a critical role in assessing natural language generation systems. Existing meta-evaluation primarily measures agreement with human…
Extending the Horizon of Early Diagnosis: Lung Cancer Prediction with Vision Transformers
Olivera Kotevska, Ian Goethert, Michael McGee +11
Lung cancer remains a leading cause of cancer-related mortality worldwide, and early diagnosis is critical for improving survival. However, early-stage malignancies can be subtle o…
Signal-based Model Access Risk Analysis for AI System Operations Security
Maria Mahbub, Steven Young, Amir Sadovnik +4
Artificial intelligence (AI) systems are now ubiquitous across domains such as security, finance, healthcare, consumer technology, and large-scale cloud services, where they proces…
A Multi-Stage Validation Framework for Trustworthy Large-scale Clinical Information Extraction using Large Language Models
Maria Mahbub, Gregory M. Dams, Josh Arnold +9
Large language models (LLMs) show promise for extracting clinically meaningful information from unstructured health records, yet their translation into real-world settings is const…
ORCHID: Orchestrated Retrieval-Augmented Classification with Human-in-the-Loop Intelligent Decision-Making for High-Risk Property
Maria Mahbub, Vanessa Lama, Sanjay Das +6
High-Risk Property (HRP) classification is critical at U.S. Department of Energy (DOE) sites, where inventories include sensitive and often dual-use equipment. Compliance must trac…
HEMERA: A Human-Explainable Transformer Model for Estimating Lung Cancer Risk using GWAS Data
Maria Mahbub, Robert J. Klein, Myvizhi Esai Selvan +12
Lung cancer (LC) is the third most common cancer and the leading cause of cancer deaths in the US. Although smoking is the primary risk factor, the occurrence of LC in never-smoker…
Adaptive Anomaly Detection for Identifying Attacks in Cyber-Physical Systems: A Systematic Literature Review
Pablo Moriano, Steven C. Hespeler, Mingyan Li +1
Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods which focused on characterizing past threats. Adapti…
Advancing NLP Security by Leveraging LLMs as Adversarial Engines
Sudarshan Srinivasan, Maria Mahbub, Amir Sadovnik
This position paper proposes a novel approach to advancing NLP security by leveraging Large Language Models (LLMs) as engines for generating diverse adversarial attacks. Building u…
Hiding-in-Plain-Sight (HiPS) Attack on CLIP for Targetted Object Removal from Images
Arka Daw, Megan Hong-Thanh Chung, Maria Mahbub +1
Machine learning models are known to be vulnerable to adversarial attacks, but traditional attacks have mostly focused on single-modalities. With the rise of large multi-modal mode…
Leveraging Large Language Models to Extract Information on Substance Use Disorder Severity from Clinical Notes: A Zero-shot Learning Approach
Maria Mahbub, Gregory M. Dams, Sudarshan Srinivasan +4
Substance use disorder (SUD) poses a major concern due to its detrimental effects on health and society. SUD identification and treatment depend on a variety of factors such as sev…
Dynamic Q&A of Clinical Documents with Large Language Models
Ran Elgedawy, Ioana Danciu, Maria Mahbub +1
Electronic health records (EHRs) house crucial patient data in clinical notes. As these notes grow in volume and complexity, manual extraction becomes challenging. This work introd…
Bengali Fake Reviews: A Benchmark Dataset and Detection System
G. M. Shahariar, Md. Tanvir Rouf Shawon, Faisal Muhammad Shah +2
The proliferation of fake reviews on various online platforms has created a major concern for both consumers and businesses. Such reviews can deceive customers and cause damage to…
Question-Answering System Extracts Information on Injection Drug Use from Clinical Notes
Maria Mahbub, Ian Goethert, Ioana Danciu +9
Background: Injection drug use (IDU) is a dangerous health behavior that increases mortality and morbidity. Identifying IDU early and initiating harm reduction interventions can be…
Bengali Fake Review Detection using Semi-supervised Generative Adversarial Networks
Md. Tanvir Rouf Shawon, G. M. Shahariar, Faisal Muhammad Shah +2
This paper investigates the potential of semi-supervised Generative Adversarial Networks (GANs) to fine-tune pretrained language models in order to classify Bengali fake reviews fr…
BioADAPT-MRC: Adversarial Learning-based Domain Adaptation Improves Biomedical Machine Reading Comprehension Task
Maria Mahbub, Sudarshan Srinivasan, Edmon Begoli +1
Biomedical machine reading comprehension (biomedical-MRC) aims to comprehend complex biomedical narratives and assist healthcare professionals in retrieving information from them.…
The Sensitivity of Word Embeddings-based Author Detection Models to Semantic-preserving Adversarial Perturbations
Jeremiah Duncan, Fabian Fallas, Chris Gropp +11
Authorship analysis is an important subject in the field of natural language processing. It allows the detection of the most likely writer of articles, news, books, or messages. Th…