3 papers
cs.LG2026
Can Revealed Preferences Clarify LLM Alignment and Steering?
Khurram Yamin, Jingjing Tang, Eric Horvitz +1
LLMs are increasingly used to make or support high-stakes decisions under uncertainty, where alignment depends not only on factual accuracy but on how models weigh tradeoffs betwee…
cs.AI2026
When Agents Say One Thing and Do Another: Validating Elicited Beliefs from LLMs
Khurram Yamin, Jingjing Tang, Santiago Cortes-Gomez +3
Large language models (LLMs) are increasingly deployed in high-stakes settings where good decisions require forming beliefs over the probability of unknown outcomes. However, it is…
cs.LG2025
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…