activity
20222026
most citedSwin SMT: Global Sequential Modeling in 3D Medical Image Segmentation

3 citations · 10 across the 15 of their papers we have counts for

collaborators

15 papers

cs.LG2026

Modelpedia: A Catalog of Model Findings for the Meta-Science of AI

Franciszek Bernat, Dawid Płudowski, Michał Jan Włodarczyk +6

Scientific knowledge about AI models is produced faster than the community can organize it. Every few months a new foundation model reshapes the field and hundreds of papers, blogs…

cs.MA2026

Competitive Market Behavior of LLMs

Pawel Struski, Jakub Swistak, Inez Okulska +1

Large language models (LLMs) are increasingly deployed as economic agents, yet there is little evidence whether LLM agents are suited for participating in market mechanisms designe…

eess.IV20243 cited

Swin SMT: Global Sequential Modeling in 3D Medical Image Segmentation

Szymon Płotka, Maciej Chrabaszcz, Przemyslaw Biecek

Recent advances in Vision Transformers (ViTs) have significantly enhanced medical image segmentation by facilitating the learning of global relationships. However, these methods fa…

cs.AI2024

CNN-based explanation ensembling for dataset, representation and explanations evaluation

Weronika Hryniewska-Guzik, Luca Longo, Przemysław Biecek

Explainable Artificial Intelligence has gained significant attention due to the widespread use of complex deep learning models in high-stake domains such as medicine, finance, and…

cs.CV2024

Red-Teaming Segment Anything Model

Krzysztof Jankowski, Bartlomiej Sobieski, Mateusz Kwiatkowski +4

Foundation models have emerged as pivotal tools, tackling many complex tasks through pre-training on vast datasets and subsequent fine-tuning for specific applications. The Segment…

cs.CV20242 cited

Red Teaming Models for Hyperspectral Image Analysis Using Explainable AI

Vladimir Zaigrajew, Hubert Baniecki, Lukasz Tulczyjew +4

Remote sensing (RS) applications in the space domain demand machine learning (ML) models that are reliable, robust, and quality-assured, making red teaming a vital approach for ide…