4 papers
Low-Pass Filtering Improves Behavioral Alignment of Vision Models
Max Wolff, Thomas Klein, Evgenia Rusak +2
Despite their impressive performance on computer vision benchmarks, Deep Neural Networks (DNNs) still fall short of adequately modeling human visual behavior, as measured by error…
MentisOculi: Revealing the Limits of Reasoning with Mental Imagery
Jana Zeller, Thaddäus Wiedemer, Fanfei Li +6
Frontier models are transitioning from multimodal large language models (MLLMs) that merely ingest visual information to unified multimodal models (UMMs) capable of native interlea…
Quantifying Uncertainty in Error Consistency: Towards Reliable Behavioral Comparison of Classifiers
Thomas Klein, Sascha Meyen, Wieland Brendel +2
Benchmarking models is a key factor for the rapid progress in machine learning (ML) research. Thus, further progress depends on improving benchmarking metrics. A standard metric to…
How Aligned are Different Alignment Metrics?
Jannis Ahlert, Thomas Klein, Felix Wichmann +1
In recent years, various methods and benchmarks have been proposed to empirically evaluate the alignment of artificial neural networks to human neural and behavioral data. But how…