15 papers
Dual-Primal Graph VAEs for Noisy Label Aggregation
Patrick Stinson, Nikolaus Kriegeskorte
Inferring the ground-truth from noisy crowdsourced labels is an important theoretical and practical problem. Neural network-based methods offer an alternative to classical Bayesian…
Human-like Object Grouping in Self-supervised Vision Transformers
Hossein Adeli, Seoyoung Ahn, Andrew Luo +3
Vision foundation models trained with self-supervised objectives achieve strong performance across diverse tasks and exhibit emergent object segmentation properties. However, their…
Comparing Linear Probes with Mahalanobis Cosine Similarity
Zhuofan Josh Ying, Peter Hase, Nikolaus Kriegeskorte
Linear probes are widely used in interpretability research and often compared by cosine similarity. The Mahalanobis cosine similarity (MCS) between two directions, which reweights…
Decomposing how prompting steers behavior
Fan L. Cheng, Nikolaus Kriegeskorte
Prompting steers large language models (LLMs) and vision-language models (VLMs) without weight updates, but it remains unclear how instruction changes reshape internal representati…
Growing a Neural Network in Breadth, Depth, and Time
Eivinas Butkus, Kedar Garzón Gupta, Nikolaus Kriegeskorte
Spatial and temporal resource constraints are critical for both biological and artificial intelligent systems. Here we define differentiable cost terms for breadth, depth, and time…
Human face perception reflects inverse-generative and naturalistic discriminative objectives
Wenxuan Guo, Heiko H. Schütt, Kamila Maria Jozwik +3
The perceptual representations supporting our ability to recognize faces remain a computational mystery. Deep neural networks offer mechanistic hypotheses for human face perception…