30 citations · 77 across the 20 of their papers we have counts for
21 papers
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…
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…
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…
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…
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,…
A Novel Dataset for Keypoint Detection of quadruped Animals from Images
Prianka Banik, Lin Li, Xishuang Dong
In this paper, we studied the problem of localizing a generic set of keypoints across multiple quadruped or four-legged animal species from images. Due to the lack of large scale a…
Semi-supervised Learning for COVID-19 Image Classification via ResNet
Lucy Nwosu, Xiangfang Li, Lijun Qian +2
Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic in over 200 countries and territories, which has resulted in a great public health concern across the internationa…
Cell Type Identification from Single-Cell Transcriptomic Data via Semi-supervised Learning
Xishuang Dong, Shanta Chowdhury, Uboho Victor +2
Cell type identification from single-cell transcriptomic data is a common goal of single-cell RNA sequencing (scRNAseq) data analysis. Neural networks have been employed to identif…
Efficient Privacy Preserving Edge Computing Framework for Image Classification
Omobayode Fagbohungbe, Sheikh Rufsan Reza, Xishuang Dong +1
In order to extract knowledge from the large data collected by edge devices, traditional cloud based approach that requires data upload may not be feasible due to communication ban…
Ensemble Deep Learning on Time-Series Representation of Tweets for Rumor Detection in Social Media
Chandra Mouli Madhav Kotteti, Xishuang Dong, Lijun Qian
Social media is a popular platform for timely information sharing. One of the important challenges for social media platforms like Twitter is whether to trust news shared on them w…
Two-path Deep Semi-supervised Learning for Timely Fake News Detection
Xishuang Dong, Uboho Victor, Lijun Qian
News in social media such as Twitter has been generated in high volume and speed. However, very few of them are labeled (as fake or true news) by professionals in near real time. I…
Deep Two-path Semi-supervised Learning for Fake News Detection
Xishuang Dong, Uboho Victor, Shanta Chowdhury +1
News in social media such as Twitter has been generated in high volume and speed. However, very few of them can be labeled (as fake or true news) in a short time. In order to achie…
Hierarchical Transfer Convolutional Neural Networks for Image Classification
Xishuang Dong, Hsiang-Huang Wu, Yuzhong Yan +1
In this paper, we address the issue of how to enhance the generalization performance of convolutional neural networks (CNN) in the early learning stage for image classification. Th…