Cover Image

Understanding challenges to the interpretation of disaggregated evaluations of algorithmic fairness

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pfohl, Stephen R., Harris, Natalie, Nagpal, Chirag, Madras, David, Mhasawade, Vishwali, Salaudeen, Olawale, Dieng, Awa, Sequeira, Shannon, Arciniegas, Santiago, Sung, Lillian, Ezeanochie, Nnamdi, Cole-Lewis, Heather, Heller, Katherine, Koyejo, Sanmi, D'Amour, Alexander
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computers and Society
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Causally Inspired Regularization Enables Domain General Representations
by: Salaudeen, Olawale, et al.
Published: (2024)

Proxy Methods for Domain Adaptation
by: Tsai, Katherine, et al.
Published: (2024)

The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africa
by: Asiedu, Mercy, et al.
Published: (2024)

Transforming and Combining Rewards for Aligning Large Language Models
by: Wang, Zihao, et al.
Published: (2024)

Are Domain Generalization Benchmarks with Accuracy on the Line Misspecified?
by: Salaudeen, Olawale, et al.
Published: (2025)

Disparate Effect Of Missing Mediators On Transportability of Causal Effects
by: Mhasawade, Vishwali, et al.
Published: (2024)

Globalizing Fairness Attributes in Machine Learning: A Case Study on Health in Africa
by: Asiedu, Mercy Nyamewaa, et al.
Published: (2023)

Bias in Language Models: Beyond Trick Tests and Toward RUTEd Evaluation
by: Lum, Kristian, et al.
Published: (2024)

Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking
by: Eisenstein, Jacob, et al.
Published: (2023)

Impact on Public Health Decision Making by Utilizing Big Data Without Domain Knowledge
by: Zhang, Miao, et al.
Published: (2024)

ImageNot: A contrast with ImageNet preserves model rankings
by: Salaudeen, Olawale, et al.
Published: (2024)

Understanding Disparities in Post Hoc Machine Learning Explanation
by: Mhasawade, Vishwali, et al.
Published: (2024)

Theoretical guarantees on the best-of-n alignment policy
by: Beirami, Ahmad, et al.
Published: (2024)

Measurement to Meaning: A Validity-Centered Framework for AI Evaluation
by: Salaudeen, Olawale, et al.
Published: (2025)

Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding
by: Zheng, Jiajing, et al.
Published: (2021)

Preference Models assume Proportional Hazards of Utilities
by: Nagpal, Chirag
Published: (2025)

Nteasee: Understanding Needs in AI for Health in Africa -- A Mixed-Methods Study of Expert and General Population Perspectives
by: Asiedu, Mercy Nyamewaa, et al.
Published: (2024)

Toward an Evaluation Science for Generative AI Systems
by: Weidinger, Laura, et al.
Published: (2025)

Let's Measure Information Step-by-Step: AI-Based Evaluation Beyond Vibes
by: Robertson, Zachary, et al.
Published: (2025)

CURE: Cultural Understanding and Reasoning Evaluation - A Framework for "Thick" Culture Alignment Evaluation in LLMs
by: Vo, Truong, et al.
Published: (2025)

A Framework for Objective-Driven Dynamical Stochastic Fields
by: Zhang, Yibo Jacky, et al.
Published: (2025)

Choosing a Proxy Metric from Past Experiments
by: Tripuraneni, Nilesh, et al.
Published: (2023)

Making physical activity fun and accessible to adults with intellectual disabilities: A pilot study of a gamification intervention
by: Stéphanie Turgeon, et al.
Published: (2024)

Aggregation Hides Out-of-Distribution Generalization Failures from Spurious Correlations
by: Salaudeen, Olawale, et al.
Published: (2025)

What's in a Query: Polarity-Aware Distribution-Based Fair Ranking
by: Balagopalan, Aparna, et al.
Published: (2025)

In-Context Learning of Energy Functions
by: Schaeffer, Rylan, et al.
Published: (2024)

Discovering Implicit Large Language Model Alignment Objectives
by: Chen, Edward, et al.
Published: (2026)

High-Dimensional Markov-switching Ordinary Differential Processes
by: Tsai, Katherine, et al.
Published: (2024)

Distributional Machine Unlearning via Selective Data Removal
by: Allouah, Youssef, et al.
Published: (2025)

SCENEBench: An Audio Understanding Benchmark Grounded in Assistive and Industrial Use Cases
by: Iyer, Laya, et al.
Published: (2026)

HiFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance
by: Zhu, Junzhe, et al.
Published: (2023)

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning
by: Nagpal, Chirag, et al.
Published: (2024)

Machine Learning for Health symposium 2024 -- Findings track
by: Hegselmann, Stefan, et al.
Published: (2025)

Position: Stop Evaluating AI with Human Tests, Develop Principled, AI-specific Tests instead
by: Sühr, Tom, et al.
Published: (2025)

Motetten am Hof Maximilians II. (1527–1576)
by: Pfohl, Jonas
Published: (2022)

Reasoning Models Don't Just Think Longer, They Move Differently
by: Gjølbye, Anders, et al.
Published: (2026)

Is Backpropagation Optimal? When Synthetic Gradients Improve Sample Efficiency
by: Zhang, Yibo Jacky, et al.
Published: (2026)

The Inadequacy of Offline LLM Evaluations: A Need to Account for Personalization in Model Behavior
by: Wang, Angelina, et al.
Published: (2025)

Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting
by: Jiang, Enyi, et al.
Published: (2023)

The Illusion of Intervention: Your LLM-Simulated Experiment is an Observational Study
by: Lin, Victoria, et al.
Published: (2026)