3 papers
cs.HC2025
Reversing the Lens: Using Explainable AI to Understand Human Expertise
Roussel Rahman, Aashwin Ananda Mishra, Wan-Lin Hu
Both humans and machine learning models learn from experience, particularly in safety- and reliability-critical domains. While psychology seeks to understand human cognition, the f…
cs.LG2025
A Fragile Number Sense: Probing the Elemental Limits of Numerical Reasoning in LLMs
Roussel Rahman, Aashwin Ananda Mishra
Large Language Models (LLMs) have demonstrated remarkable emergent capabilities, yet the robustness of their numerical reasoning remains an open question. While standard benchmarks…
cs.SI2024
Network Models of Expertise in the Complex Task of Operating Particle Accelerators
Roussel Rahman, Jane Shtalenkova, Aashwin Ananda Mishra +1
We implement a network-based approach to study expertise in a complex real-world task: operating particle accelerators. Most real-world tasks we learn and perform (e.g., driving ca…