4 citations · 14 across the 13 of their papers we have counts for
8 papers · 1 filter
Aggregation Hides Out-of-Distribution Generalization Failures from Spurious Correlations
Olawale Salaudeen, Haoran Zhang, Kumail Alhamoud +2
Benchmarks for out-of-distribution (OOD) generalization frequently show a strong positive correlation between in-distribution (ID) and OOD accuracy across models, termed "accuracy-…
Position: Stop Evaluating AI with Human Tests, Develop Principled, AI-specific Tests instead
Tom Sühr, Florian E. Dorner, Olawale Salaudeen +2
Large Language Models (LLMs) have achieved remarkable results on a range of standardized tests originally designed to assess human cognitive and psychological traits, such as intel…
Are Domain Generalization Benchmarks with Accuracy on the Line Misspecified?
Olawale Salaudeen, Nicole Chiou, Shiny Weng +1
Spurious correlations, unstable statistical shortcuts a model can exploit, are expected to degrade performance out-of-distribution (OOD). However, across many popular OOD generaliz…
What's in a Query: Polarity-Aware Distribution-Based Fair Ranking
Aparna Balagopalan, Kai Wang, Olawale Salaudeen +2
Machine learning-driven rankings, where individuals (or items) are ranked in response to a query, mediate search exposure or attention in a variety of safety-critical settings. Thu…
Causally Inspired Regularization Enables Domain General Representations
Olawale Salaudeen, Sanmi Koyejo
Given a causal graph representing the data-generating process shared across different domains/distributions, enforcing sufficient graph-implied conditional independencies can ident…
ImageNot: A contrast with ImageNet preserves model rankings
Olawale Salaudeen, Moritz Hardt
We introduce ImageNot, a dataset constructed explicitly to be drastically different than ImageNet while matching its scale. ImageNot is designed to test the external validity of de…
Proxy Methods for Domain Adaptation
Katherine Tsai, Stephen R. Pfohl, Olawale Salaudeen +5
We study the problem of domain adaptation under distribution shift, where the shift is due to a change in the distribution of an unobserved, latent variable that confounds both the…
Target Conditioned Representation Independence (TCRI); From Domain-Invariant to Domain-General Representations
Olawale Salaudeen, Oluwasanmi Koyejo
We propose a Target Conditioned Representation Independence (TCRI) objective for domain generalization. TCRI addresses the limitations of existing domain generalization methods due…