5 citations · 11 across the 14 of their papers we have counts for
4 papers · 1 filter
Generate, Evaluate, Iterate: Synthetic Data for Human-in-the-Loop Refinement of LLM Judges
Hyo Jin Do, Zahra Ashktorab, Jasmina Gajcin +5
The LLM-as-a-judge paradigm enables flexible, user-defined evaluation, but its effectiveness is often limited by the scarcity of diverse, representative data for refining criteria.…
Who Sees the Risk? Stakeholder Conflicts and Explanatory Policies in LLM-based Risk Assessment
Srishti Yadav, Jasmina Gajcin, Erik Miehling +1
Understanding how different stakeholders perceive risks in AI systems is essential for their responsible deployment. This paper presents a framework for stakeholder-grounded risk a…
Interpreting LLM-as-a-Judge Policies via Verifiable Global Explanations
Jasmina Gajcin, Erik Miehling, Rahul Nair +3
Using LLMs to evaluate text, that is, LLM-as-a-judge, is increasingly being used at scale to augment or even replace human annotations. As such, it is imperative that we understand…
Agentic AI Needs a Systems Theory
Erik Miehling, Karthikeyan Natesan Ramamurthy, Kush R. Varshney +11
The endowment of AI with reasoning capabilities and some degree of agency is widely viewed as a path toward more capable and generalizable systems. Our position is that the current…