9 citations · 15 across the 6 of their papers we have counts for
3 papers · 1 filter
Transparent AI: The Case for Interpretability and Explainability
Dhanesh Ramachandram, Himanshu Joshi, Judy Zhu +3
As artificial intelligence systems increasingly inform high-stakes decisions across sectors, transparency has become foundational to responsible and trustworthy AI implementation.…
LinguaMark: Do Multimodal Models Speak Fairly? A Benchmark-Based Evaluation
Ananya Raval, Aravind Narayanan, Vahid Reza Khazaie +1
Large Multimodal Models (LMMs) are typically trained on vast corpora of image-text data but are often limited in linguistic coverage, leading to biased and unfair outputs across la…
CRISP-NAM: Competing Risks Interpretable Survival Prediction with Neural Additive Models
Dhanesh Ramachandram, Ananya Raval
Competing risks are crucial considerations in survival modelling, particularly in healthcare domains where patients may experience multiple distinct event types. We propose CRISP-N…