358 citations · 1k across the 34 of their papers we have counts for
10 papers · 1 filter
Resource Constraints and Performance in Agentic AI Systems
Amaz Salman, Malka Halgamuge, Teo Susnjak
Progress toward more autonomous AI increasingly depends on agentic systems that combine a language model with tools, memory, state management, and multi-step execution. These mecha…
Constructing Executable Analytical Knowledge Representations for Meta-Analysis Synthesis Using an Agentic Harness
Lingbo Li, Anuradha Mathrani, Teo Susnjak
Meta-analysis synthesis highlights a fundamental challenge in knowledge-based scientific analysis: structured evidence does not by itself represent the analytical knowledge require…
Forecasting Commencing Enrolments Under Data Sparsity: A Zero-Shot Time Series Foundation Models Framework for Higher Education Planning
Jittarin Jetwiriyanon, Teo Susnjak, Surangika Ranathunga
Effective resource allocation in higher education depends on reliable enrolment forecasts, yet institutional planners frequently face data series disrupted by structural shifts. Th…
Automated Risk-of-Bias Assessment of Randomized Controlled Trials: A First Look at a GEPA-trained Programmatic Prompting Framework
Lingbo Li, Anuradha Mathrani, Teo Susnjak
Assessing risk of bias (RoB) in randomized controlled trials is essential for trustworthy evidence synthesis, but the process is resource-intensive and prone to variability across…
Transforming Evidence Synthesis: A Systematic Review of the Evolution of Automated Meta-Analysis in the Age of AI
Lingbo Li, Anuradha Mathrani, Teo Susnjak
Exponential growth in scientific literature has heightened the demand for efficient evidence-based synthesis, driving the rise of the field of Automated Meta-analysis (AMA) powered…
Image First or Text First? Optimising the Sequencing of Modalities in Large Language Model Prompting and Reasoning Tasks
Grant Wardle, Teo Susnjak
This paper examines how the sequencing of images and text within multi-modal prompts influences the reasoning performance of large language models (LLMs). We performed empirical ev…
Over the Edge of Chaos? Excess Complexity as a Roadblock to Artificial General Intelligence
Teo Susnjak, Timothy R. McIntosh, Andre L. C. Barczak +4
In this study, we explored the progression trajectories of artificial intelligence (AI) systems through the lens of complexity theory. We challenged the conventional linear and exp…
Inadequacies of Large Language Model Benchmarks in the Era of Generative Artificial Intelligence
Timothy R. McIntosh, Teo Susnjak, Nalin Arachchilage +3
The rapid rise in popularity of Large Language Models (LLMs) with emerging capabilities has spurred public curiosity to evaluate and compare different LLMs, leading many researcher…
From Google Gemini to OpenAI Q* (Q-Star): A Survey of Reshaping the Generative Artificial Intelligence (AI) Research Landscape
Timothy R. McIntosh, Teo Susnjak, Tong Liu +2
This comprehensive survey explored the evolving landscape of generative Artificial Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts (MoE…
ChatGPT: The End of Online Exam Integrity?
Teo Susnjak
This study evaluated the ability of ChatGPT, a recently developed artificial intelligence (AI) agent, to perform high-level cognitive tasks and produce text that is indistinguishab…