3 papers
cs.AI2026
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…
cs.CV2026
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…
q-bio.NC2025
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…