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Philipp Alexander Kreer

2 accepted papers

2026

Bayesian Influence Functions for Hessian-Free Data Attribution

ICLR 2026poster

Classical influence functions face significant challenges when applied to deep neural networks, primarily due to non-invertible Hessians and high-dimensional parameter spaces. We propose the local Bayesian influence function (BIF), an extension of classical influence functions that replaces Hessian…

Cited by 0SourceScholar
2025

Noise Injection Reveals Hidden Capabilities of Sandbagging Language Models

NeurIPS 2025poster

Capability evaluations play a crucial role in assessing and regulating frontier AI systems. The effectiveness of these evaluations faces a significant challenge: strategic underperformance, or ``sandbagging'', where models deliberately underperform during evaluation. Sandbagging can manifest either…

Cited by 0SourcecodeScholar