Fanfei Li — accepted AI-conference papers

2026

MentisOculi: Revealing the Limits of Reasoning with Mental Imagery

Jana Zeller, Thaddäus Wiedemer, Fanfei Li, Thomas Klein, Prasanna Mayilvahanan, Matthias Bethge +3

ICML 2026poster

Frontier models are transitioning from _multimodal large language models_ (MLLMs) that merely ingest visual information to _unified multimodal models_ (UMMs) capable of native interleaved generation. This shift has sparked interest in using intermediate visualizations as a reasoning aid, akin to hum…

Cited by 0 Source ↗Scholar ↗

2025

LAION-C: An Out-of-Distribution Benchmark for Web-Scale Vision Models

Fanfei Li, Thomas Klein, Wieland Brendel, Robert Geirhos, Roland S. Zimmermann

ICML 2025poster

Out-of-distribution (OOD) robustness is a desired property of computer vision models. Improving model robustness requires high-quality signals from robustness benchmarks to quantify progress. While various benchmark datasets such as ImageNet-C were proposed in the ImageNet era, most ImageNet-C corru…

Cited by 0 Source ↗PDF ↗Scholar ↗