5 citations · 5 across the 4 of their papers we have counts for
4 papers
KANEx: Translating Kolmogorov-Arnold Networks' Interpretability to Medical Explainability
Krithi Shailya, Ananya Lakshmi Ravi, Venkatanathan K. V. +4
Computer vision models have become highly effective for medical applications, yet their black-box nature continues to undermine clinician trust. In clinical workflows, chest X-ray…
mFARM: Towards Multi-Faceted Fairness Assessment based on HARMs in Clinical Decision Support
Shreyash Adappanavar, Krithi Shailya, Gokul S Krishnan +2
The deployment of Large Language Models (LLMs) in high-stakes medical settings poses a critical AI alignment challenge, as models can inherit and amplify societal biases, leading t…
Where Should I Study? Biased Language Models Decide! Evaluating Fairness in LMs for Academic Recommendations
Krithi Shailya, Akhilesh Kumar Mishra, Gokul S Krishnan +1
Large Language Models (LLMs) are increasingly used as daily recommendation systems for tasks like education planning, yet their recommendations risk perpetuating societal biases. T…
LExT: Towards Evaluating Trustworthiness of Natural Language Explanations
Krithi Shailya, Shreya Rajpal, Gokul S Krishnan +1
As Large Language Models (LLMs) become increasingly integrated into high-stakes domains, there have been several approaches proposed toward generating natural language explanations…