4 papers
The Impossibility of Inverse Permutation Learning in Transformer Models
Rohan Alur, Chris Hays, Manish Raghavan +1
In this technical note, we study the problem of inverse permutation learning in decoder-only transformers. Given a permutation and a string to which that permutation has been appli…
Double Machine Learning for Causal Inference under Shared-State Interference
Chris Hays, Manish Raghavan
Researchers and practitioners often wish to measure treatment effects in settings where units interact via markets and recommendation systems. In these settings, units are affected…
Inducing Efficient and Equitable Professional Networks through Link Recommendations
Cynthia Dwork, Chris Hays, Lunjia Hu +2
Professional networks are a key determinant of individuals' labor market outcomes. They may also play a role in either exacerbating or ameliorating inequality of opportunity across…
From Fairness to Infinity: Outcome-Indistinguishable (Omni)Prediction in Evolving Graphs
Cynthia Dwork, Chris Hays, Nicole Immorlica +2
Professional networks provide invaluable entree to opportunity through referrals and introductions. A rich literature shows they also serve to entrench and even exacerbate a status…