2 papers
math.NA2026
On the Limits of Interpretable Machine Learning in Quintic Root Classification
Rohan Thomas, Majid Bani-Yaghoub
Can Machine Learning (ML) autonomously recover interpretable mathematical structure from raw numerical data? We aim to answer this question using the classification of real-root co…
cs.AI2026
ProMoral-Bench: Evaluating Prompting Strategies for Moral Reasoning and Safety in LLMs
Rohan Subramanian Thomas, Shikhar Shiromani, Abdullah Chaudhry +4
Prompt design significantly impacts the moral competence and safety alignment of large language models (LLMs), yet empirical comparisons remain fragmented across datasets and model…