25 citations · 44 across the 6 of their papers we have counts for
6 papers
Hallucination Detection and Mitigation in Large Language Models
Ahmad Pesaranghader, Erin Li
Large Language Models (LLMs) and Large Reasoning Models (LRMs) offer transformative potential for high-stakes domains like finance and law, but their tendency to hallucinate, gener…
Modeling electronic health record data using a knowledge-graph-embedded topic model
Yuesong Zou, Ahmad Pesaranghader, Aman Verma +2
The rapid growth of electronic health record (EHR) datasets opens up promising opportunities to understand human diseases in a systematic way. However, effective extraction of clin…
CT-SGAN: Computed Tomography Synthesis GAN
Ahmad Pesaranghader, Yiping Wang, Mohammad Havaei
Diversity in data is critical for the successful training of deep learning models. Leveraged by a recurrent generative adversarial network, we propose the CT-SGAN model that genera…
Dual Adversarial Inference for Text-to-Image Synthesis
Qicheng Lao, Mohammad Havaei, Ahmad Pesaranghader +3
Synthesizing images from a given text description involves engaging two types of information: the content, which includes information explicitly described in the text (e.g., color,…
One Single Deep Bidirectional LSTM Network for Word Sense Disambiguation of Text Data
Ahmad Pesaranghader, Ali Pesaranghader, Stan Matwin +1
Due to recent technical and scientific advances, we have a wealth of information hidden in unstructured text data such as offline/online narratives, research articles, and clinical…
TrajectoryNet: An Embedded GPS Trajectory Representation for Point-based Classification Using Recurrent Neural Networks
Xiang Jiang, Erico N de Souza, Ahmad Pesaranghader +3
Understanding and discovering knowledge from GPS (Global Positioning System) traces of human activities is an essential topic in mobility-based urban computing. We propose Trajecto…