5 citations · 11 across the 14 of their papers we have counts for
3 papers · 1 filter
FactCorrector: A Graph-Inspired Approach to Long-Form Factuality Correction of Large Language Models
Javier Carnerero-Cano, Massimiliano Pronesti, Radu Marinescu +6
Large language models (LLMs) are widely used in knowledge-intensive applications but often generate factually incorrect responses. A promising approach to rectify these flaws is co…
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…