8 papers
High-Stakes Decisions with Language Models: Insights from Emergency Triage
Khurram Yamin, Christopher Kelly, Bryan Wilder +1
High-stakes decisions under uncertainty, such as medical emergency triage, require more than accurate predictions. They depend on estimating the likelihood of alternative outcomes…
What Must Generalist Agents Remember?
Khurram Yamin, Namrata Deka, Maitreyi Swaroop +3
This paper develops a formal account of what generalist agents must store in memory in order to act near-optimally across multiple environments and goals. It shows that when two do…
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…
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…
Can LLMs Reconcile Knowledge Conflicts in Counterfactual Reasoning
Khurram Yamin, Gaurav Ghosal, Bryan Wilder
Large Language Models have been shown to contain extensive world knowledge in their parameters, enabling impressive performance on many knowledge intensive tasks. However, when dep…
Dependent Randomized Rounding for Budget Constrained Experimental Design
Khurram Yamin, Edward Kennedy, Bryan Wilder
Policymakers in resource-constrained settings require experimental designs that satisfy strict budget limits while ensuring precise estimation of treatment effects. We propose a fr…