1 citations · 2 across the 9 of their papers we have counts for
9 papers
Silent Failures in Agent-Tool Interaction: An Audit of ToolUniverse
Shreya Gopalan, Devansh Singh, Sundaraparipurnan Narayanan
Agentic AI systems are increasingly adopting automated pipelines that integrate multiple tools. While prior research have studied task success and task completion of such agentic s…
Beyond Accuracy and Surface Fluency: Risk-Sensitive Evaluation of LLMs for Legal Clause Generation
Devansh Singh, Sundaraparipurnan Narayanan
Large language models (LLMs) are increasingly used to draft contractual language, yet conventional accuracy or preference-based evaluations are poorly matched to legal drafting. A…
Designing for Ethical AI: HCI Feature Considerations to Improve Fairness and User Experience in AutoML use for Human Resources
Sundaraparipurnan Narayanan
This thesis examines the fairness of Automated Machine Learning (AutoML) tools in human resource hiring systems through the combined lenses of regulation, business strategy, and Hu…
Unmasking the Reality of PII Masking Models: Performance Gaps and the Call for Accountability
Devansh Singh, Sundaraparipurnan Narayanan
Privacy Masking is a critical concept under data privacy involving anonymization and de-anonymization of personally identifiable information (PII). Privacy masking techniques rely…
Decoding the Digital Fine Print: Navigating the potholes in Terms of service/ use of GenAI tools against the emerging need for Transparent and Trustworthy Tech Futures
Sundaraparipurnan Narayanan
The research investigates the crucial role of clear and intelligible terms of service in cultivating user trust and facilitating informed decision-making in the context of AI, in s…
GUARD-D-LLM: An LLM-Based Risk Assessment Engine for the Downstream uses of LLMs
sundaraparipurnan Narayanan, Sandeep Vishwakarma
Amidst escalating concerns about the detriments inflicted by AI systems, risk management assumes paramount importance, notably for high-risk applications as demanded by the Europea…
A risk-based approach to assessing liability risk for AI-driven harms considering EU liability directive
Sundaraparipurnan Narayanan, Mark Potkewitz
Artificial intelligence can cause inconvenience, harm, or other unintended consequences in various ways, including those that arise from defects or malfunctions in the AI system it…
Democratize with Care: The need for fairness specific features in user-interface based open source AutoML tools
Sundaraparipurnan Narayanan
AI is increasingly playing a pivotal role in businesses and organizations, impacting the outcomes and interests of human users. Automated Machine Learning (AutoML) streamlines the…
On the notion of Hallucinations from the lens of Bias and Validity in Synthetic CXR Images
Gauri Bhardwaj, Yuvaraj Govindarajulu, Sundaraparipurnan Narayanan +2
Medical imaging has revolutionized disease diagnosis, yet the potential is hampered by limited access to diverse and privacy-conscious datasets. Open-source medical datasets, while…