5 citations · 13 across the 10 of their papers we have counts for
10 papers
Judging LLM-as-a-Judge: Concerning Rubric Artifacts in LLM-based Automated Text Generation Evaluation
Anshul Bagaria, Sowmya S Sundaram, Gokul S Krishnan +1
LLM-as-a-Judge pipelines are increasingly used to evaluate AI-generated text, based on the assumption that judgments arise from reasoning over candidate responses with respect to a…
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…
IndiCASA: A Dataset and Bias Evaluation Framework in LLMs Using Contrastive Embedding Similarity in the Indian Context
Santhosh G S, Akshay Govind S, Gokul S Krishnan +2
Large Language Models (LLMs) have gained significant traction across critical domains owing to their impressive contextual understanding and generative capabilities. However, their…
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…
Participatory Approaches in AI Development and Governance: Case Studies
Ambreesh Parthasarathy, Aditya Phalnikar, Gokul S Krishnan +2
This paper forms the second of a two-part series on the value of a participatory approach to AI development and deployment. The first paper had crafted a principled, as well as pra…
Participatory Approaches in AI Development and Governance: A Principled Approach
Ambreesh Parthasarathy, Aditya Phalnikar, Ameen Jauhar +3
The widespread adoption of Artificial Intelligence (AI) technologies in the public and private sectors has resulted in them significantly impacting the lives of people in new and u…
InSaAF: Incorporating Safety through Accuracy and Fairness | Are LLMs ready for the Indian Legal Domain?
Yogesh Tripathi, Raghav Donakanti, Sahil Girhepuje +7
Recent advancements in language technology and Artificial Intelligence have resulted in numerous Language Models being proposed to perform various tasks in the legal domain ranging…
LineConGraphs: Line Conversation Graphs for Effective Emotion Recognition using Graph Neural Networks
Gokul S Krishnan, Sarala Padi, Craig S. Greenberg +3
Emotion Recognition in Conversations (ERC) is a critical aspect of affective computing, and it has many practical applications in healthcare, education, chatbots, and social media…