1 citations · 2 across the 4 of their papers we have counts for
4 papers
OBLIQ-Bench: Exposing Overlooked Bottlenecks in Modern Retrievers with Latent and Implicit Queries
Diane Tchuindjo, Devavrat Shah, Omar Khattab
Retrieval benchmarks are increasingly saturating, but we argue that efficient search is far from a solved problem. We identify a class of queries we call oblique, which seek docume…
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…
Integrating Expert Judgment and Algorithmic Decision Making: An Indistinguishability Framework
Rohan Alur, Loren Laine, Darrick K. Li +3
We introduce a novel framework for human-AI collaboration in prediction and decision tasks. Our approach leverages human judgment to distinguish inputs which are algorithmically in…
Human Expertise in Algorithmic Prediction
Rohan Alur, Manish Raghavan, Devavrat Shah
We introduce a novel framework for incorporating human expertise into algorithmic predictions. Our approach leverages human judgment to distinguish inputs which are algorithmically…