5 papers
Beyond Morphology: Quantifying the Diagnostic Power of Color Features in Cancer Classification
Farnaz Kheiri, Shahryar Rahnamayan, Masoud Makrehchi
In histopathology, human experts primarily rely on color as a means of enhancing contrast to interpret tissue morphology, whereas machine vision models process color as raw statist…
The Impact of Role Design in In-Context Learning for Large Language Models
Hamidreza Rouzegar, Masoud Makrehchi
In-context learning (ICL) enables Large Language Models (LLMs) to generate predictions based on prompts without additional fine-tuning. While prompt engineering has been widely stu…
Enhancing Diversity in Multi-objective Feature Selection
Sevil Zanjani Miyandoab, Shahryar Rahnamayan, Azam Asilian Bidgoli +2
Feature selection plays a pivotal role in the data preprocessing and model-building pipeline, significantly enhancing model performance, interpretability, and resource efficiency a…
Generative AI for Enhancing Active Learning in Education: A Comparative Study of GPT-3.5 and GPT-4 in Crafting Customized Test Questions
Hamdireza Rouzegar, Masoud Makrehchi
This study investigates how LLMs, specifically GPT-3.5 and GPT-4, can develop tailored questions for Grade 9 math, aligning with active learning principles. By utilizing an iterati…
Enhancing Text Classification through LLM-Driven Active Learning and Human Annotation
Hamidreza Rouzegar, Masoud Makrehchi
In the context of text classification, the financial burden of annotation exercises for creating training data is a critical issue. Active learning techniques, particularly those r…