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Ryan Brown

3 accepted papers

2026

The Heterogeneous Safety Impacts of Benign Multilingual Fine-Tuning

ICML 2026poster

Fine-tuning a large language model is a ubiquitous method for enhancing its capability on a specific downstream task. However, prior work has shown that this increase in capability comes with a cost: it can increase a model's tendency to respond to unsafe adversarial prompts, even when fine-tuning w…

Cited by 0SourceScholar
2025

FairImagen: Post-Processing for Bias Mitigation in Text-to-Image Models

NeurIPS 2025poster

Text-to-image diffusion models, such as Stable Diffusion, have demonstrated remarkable capabilities in generating high-quality and diverse images from natural language prompts. However, recent studies reveal that these models often replicate and amplify societal biases, particularly along demographi…

Cited by 0SourcecodeScholar
2021

Fair Influence Maximization: a Welfare Optimization Approach

AAAI 2021technical

Several behavioral, social, and public health interventions, such as suicide/HIV prevention or community preparedness against natural disasters, leverage social network information to maximize outreach. Algorithmic influence maximization techniques have been proposed to aid with the choice of ``peer…

Cited by 65SourcePDFScholar