4 papers
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…
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…
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…
Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys
Nathan Johnson, Aashwin Ananda Mishra, Apurva Mehta
The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demandin…