1 citations · 1 across the 3 of their papers we have counts for
4 papers
Do LLMs Track Public Opinion? A Multi-Model Study of Favorability Predictions in the 2024 U.S. Presidential Election
Riya Parikh, Sarah H. Cen, Chara Podimata
We investigate whether Large Language Models (LLMs) can track public opinion as measured by exit polls during the 2024 U.S. presidential election cycle. Our analysis focuses on hea…
Contextual Dynamic Pricing with Heterogeneous Buyers
Thodoris Lykouris, Sloan Nietert, Princewill Okoroafor +2
We initiate the study of contextual dynamic pricing with a heterogeneous population of buyers, where a seller repeatedly posts prices (over rounds) that depend on the observabl…
Large-Scale, Longitudinal Study of Large Language Models During the 2024 US Election Season
Sarah H. Cen, Andrew Ilyas, Hedi Driss +4
The 2024 US presidential election is the first major contest to occur in the US since the popularization of large language models (LLMs). Building on lessons from earlier shifts in…
Incentive-Aware Machine Learning; Robustness, Fairness, Improvement & Causality
Chara Podimata
The article explores the emerging domain of incentive-aware machine learning (ML), which focuses on algorithmic decision-making in contexts where individuals can strategically modi…