3 papers
cs.LG2026
A Structural Theory of Position Bias in Transformers
Hanna Herasimchyk, Robin Labryga, Tomislav Prusina +1
Transformer models systematically favor certain token positions, yet the architectural origins of this position bias remain poorly understood. This bias is closely connected to the…
cs.CL2025
Prediction is not Explanation: Revisiting the Explanatory Capacity of Mapping Embeddings
Hanna Herasimchyk, Alhassan Abdelhalim, Sören Laue +1
Understanding what knowledge is implicitly encoded in deep learning models is essential for improving the interpretability of AI systems. This paper examines common methods to expl…
cs.CV2025
Multi-Label Plant Species Prediction with Metadata-Enhanced Multi-Head Vision Transformers
Hanna Herasimchyk, Robin Labryga, Tomislav Prusina
We present a multi-head vision transformer approach for multi-label plant species prediction in vegetation plot images, addressing the PlantCLEF 2025 challenge. The task involves t…