7 citations · 19 across the 19 of their papers we have counts for
22 papers
Mind the Refinement Gap: When Safe High-Level Robot Plans Produce Unsafe Executions
Stabak Das, Priyesh Ranjan, Xiangfang Li +1
Language-enabled robot systems increasingly combine semantic-graph planning with temporal-logic safety monitors. We investigate a trace-completeness assumption in these systems: wh…
Calibrated RF-Fingerprinting Under Interference With Heterogeneous Transmission Protocols
Tariq Abdul-Quddoos, Xiangfang Li, Lijun Qian
Radio Frequency(RF)-Fingerprinting is a spectrum monitoring technique that identifies specific transmitters based on hardware impairments imprinted within the emitted signal. Altho…
UA-ChatDev: Uncertainty-Aware Multi-Agent Collaboration for Reliable Software Development
Temitayo Olamilekan Ogunsusi, Lijun Qian, Xishuang Dong
Software development is a complex task that demands cooperation among agents with diverse roles. Large language models (LLMs) have enabled autonomous multi-agent software developme…
Multi-task GINN-LP for Multi-target Symbolic Regression
Hussein Rajabu, Lijun Qian, Xishuang Dong
In the area of explainable artificial intelligence, Symbolic Regression (SR) has emerged as a promising approach by discovering interpretable mathematical expressions that fit data…
Transmitter Identification and Protocol Categorization in Shared Spectrum via Multi-Task RF Classification at the Network Edge
Tariq Abdul-Quddoos, Tasnia Sharmin, Xiangfang Li +1
As spectrum sharing becomes increasingly vital to meet rising wireless demands in the future, spectrum monitoring and transmitter identification are indispensable for enforcing spe…
Systematic Comparative Analysis of Large Pretrained Language Models on Contextualized Medication Event Extraction
Tariq Abdul-Quddoos, Xishuang Dong, Lijun Qian
Attention-based models have become the leading approach in modeling medical language for Natural Language Processing (NLP) in clinical notes. These models outperform traditional te…
Enhancing Learning Path Recommendation via Multi-task Learning
Afsana Nasrin, Lijun Qian, Pamela Obiomon +1
Personalized learning is a student-centered educational approach that adapts content, pace, and assessment to meet each learner's unique needs. As the key technique to implement th…
Ensemble BERT for Medication Event Classification on Electronic Health Records (EHRs)
Shouvon Sarker, Xishuang Dong, Lijun Qian
Identification of key variables such as medications, diseases, relations from health records and clinical notes has a wide range of applications in the clinical domain. n2c2 2022 p…
Knowledge Acquisition on Mass-shooting Events via LLMs for AI-Driven Justice
Benign John Ihugba, Afsana Nasrin, Ling Wu +3
Mass-shooting events pose a significant challenge to public safety, generating large volumes of unstructured textual data that hinder effective investigations and the formulation o…
Data Augmentation via Diffusion Model to Enhance AI Fairness
Christina Hastings Blow, Lijun Qian, Camille Gibson +2
AI fairness seeks to improve the transparency and explainability of AI systems by ensuring that their outcomes genuinely reflect the best interests of users. Data augmentation, whi…
Deep Knowledge Tracing for Personalized Adaptive Learning at Historically Black Colleges and Universities
Ming-Mu Kuo, Xiangfang Li, Lijun Qian +2
Personalized adaptive learning (PAL) stands out by closely monitoring individual students' progress and tailoring their learning paths to their unique knowledge and needs. A crucia…
Enhancing LLM Fine-tuning for Text-to-SQLs by SQL Quality Measurement
Shouvon Sarker, Xishuang Dong, Xiangfang Li +1
Text-to-SQLs enables non-expert users to effortlessly retrieve desired information from relational databases using natural language queries. While recent advancements, particularly…
Enhancing Deep Knowledge Tracing via Diffusion Models for Personalized Adaptive Learning
Ming Kuo, Shouvon Sarker, Lijun Qian +3
In contrast to pedagogies like evidence-based teaching, personalized adaptive learning (PAL) distinguishes itself by closely monitoring the progress of individual students and tail…
Comprehensive Validation on Reweighting Samples for Bias Mitigation via AIF360
Christina Hastings Blow, Lijun Qian, Camille Gibson +2
Fairness AI aims to detect and alleviate bias across the entire AI development life cycle, encompassing data curation, modeling, evaluation, and deployment-a pivotal aspect of ethi…
Medical Data Augmentation via ChatGPT: A Case Study on Medication Identification and Medication Event Classification
Shouvon Sarker, Lijun Qian, Xishuang Dong
The identification of key factors such as medications, diseases, and relationships within electronic health records and clinical notes has a wide range of applications in the clini…
Inverse Quantum Fourier Transform Inspired Algorithm for Unsupervised Image Segmentation
Taoreed Akinola, Xiangfang Li, Richard Wilkins +2
Image segmentation is a very popular and important task in computer vision. In this paper, inverse quantum Fourier transform (IQFT) for image segmentation has been explored and a n…
Calibrated Bagging Deep Learning for Image Semantic Segmentation: A Case Study on COVID-19 Chest X-ray Image
Lucy Nwosu, Xiangfang Li, Lijun Qian +2
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). Imaging tests such as chest X-ray (CXR) and computed tomography (CT) can pr…
Federated Spectrum Learning for Reconfigurable Intelligent Surfaces-Aided Wireless Edge Networks
Bo Yang, Xuelin Cao, Chongwen Huang +6
Increasing concerns on intelligent spectrum sensing call for efficient training and inference technologies. In this paper, we propose a novel federated learning (FL) framework, dub…
Effect of Batch Normalization on Noise Resistant Property of Deep Learning Models
Omobayode Fagbohungbe, Lijun Qian
The fast execution speed and energy efficiency of analog hardware has made them a strong contender for deployment of deep learning model at the edge. However, there are concerns ab…
Impact of Learning Rate on Noise Resistant Property of Deep Learning Models
Omobayode Fagbohungbe, Lijun Qian
The interest in analog computation has grown tremendously in recent years due to its fast computation speed and excellent energy efficiency, which is very important for edge and Io…
Impact of L1 Batch Normalization on Analog Noise Resistant Property of Deep Learning Models
Omobayode Fagbohungbe, Lijun Qian
Analog hardware has become a popular choice for machine learning on resource-constrained devices recently due to its fast execution and energy efficiency. However, the inherent pre…
Integrating Human-in-the-loop into Swarm Learning for Decentralized Fake News Detection
Xishuang Dong, Lijun Qian
Social media has become an effective platform to generate and spread fake news that can mislead people and even distort public opinion. Centralized methods for fake news detection,…