2 citations · 4 across the 11 of their papers we have counts for
6 papers · 1 filter
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…
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…
Accounting for Missing Covariates in Heterogeneous Treatment Estimation
Khurram Yamin, Vibhhu Sharma, Ed Kennedy +1
Many applications of causal inference require using treatment effects estimated on a study population to make decisions in a separate target population. We consider the challenging…
Failure Modes of LLMs for Causal Reasoning on Narratives
Khurram Yamin, Shantanu Gupta, Gaurav R. Ghosal +2
The ability to robustly identify causal relationships is essential for autonomous decision-making and adaptation to novel scenarios. However, accurately inferring causal structure…
Novelty Detection for Election Fraud: A Case Study with Agent-Based Simulation Data
Khurram Yamin, Nima Jadali, Dima Nazzal +1
In this paper, we propose a robust election simulation model and independently developed election anomaly detection algorithm that demonstrates the simulation's utility. The simula…
Online Detection Of Supply Chain Network Disruptions Using Sequential Change-Point Detection for Hawkes Processes
Khurram Yamin, Haoyun Wang, Benoit Montreuil +1
In this paper, we attempt to detect an inflection or change-point resulting from the Covid-19 pandemic on supply chain data received from a large furniture company. To accomplish t…