2 citations · 2 across the 4 of their papers we have counts for
4 papers
Justified or Just Convincing? Error Verifiability as a Dimension of LLM Quality
Xiaoyuan Zhu, Kimberly Le Truong, Riccardo Fogliato +8
As LLMs are deployed in high-stakes settings, users must judge the correctness of individual responses, often relying on model-generated justifications such as reasoning chains or…
Predicting Language Models' Success at Zero-Shot Probabilistic Prediction
Kevin Ren, Santiago Cortes-Gomez, Carlos Miguel Patiño +7
Recent work has investigated the capabilities of large language models (LLMs) as zero-shot models for generating individual-level characteristics (e.g., to serve as risk models or…
Validating LLM-as-a-Judge Systems under Rating Indeterminacy
Luke Guerdan, Solon Barocas, Kenneth Holstein +3
The LLM-as-a-judge paradigm, in which a judge LLM system replaces human raters in rating the outputs of other generative AI (GenAI) systems, plays a critical role in scaling and st…
Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantification
Santiago Cortes-Gomez, Carlos Patiño, Yewon Byun +3
Interest has been growing in decision-focused machine learning methods which train models to account for how their predictions are used in downstream optimization problems. Doing s…