1 citations · 1 across the 5 of their papers we have counts for
5 papers
You Don't Need Prompt Engineering Anymore: The Prompting Inversion
Imran Khan
Prompt engineering, particularly Chain-of-Thought (CoT) prompting, significantly enhances LLM reasoning capabilities. We introduce "Sculpting," a constrained, rule-based prompting…
From Literal to Liberal: A Meta-Prompting Framework for Eliciting Human-Aligned Exception Handling in Large Language Models
Imran Khan
Large Language Models (LLMs) are increasingly being deployed as the reasoning engines for agentic AI systems, yet they exhibit a critical flaw: a rigid adherence to explicit rules…
[Social] Allostasis: Or, How I Learned To Stop Worrying and Love The Noise
Imran Khan
The notion of homeostasis typically conceptualises biological and artificial systems as maintaining stability by resisting deviations caused by environmental and social perturbatio…
Harnessing IoT and Generative AI for Weather-Adaptive Learning in Climate Resilience Education
Imran S. A. Khan, Emmanuel G. Blanchard, Sébastien George
This paper introduces the Future Atmospheric Conditions Training System (FACTS), a novel platform that advances climate resilience education through place-based, adaptive learning…
Analyzing Compression Techniques for Computer Vision
Maniratnam Mandal, Imran Khan
Compressing deep networks is highly desirable for practical use-cases in computer vision applications. Several techniques have been explored in the literature, and research has bee…