7 citations · 8 across the 8 of their papers we have counts for
8 papers
A feedback control optimizer for online and hardware-aware training of Spiking Neural Networks
Matteo Saponati, Chiara De Luca, Giacomo Indiveri +1
Unlike traditional artificial neural networks (ANNs), biological neuronal networks solve complex cognitive tasks with sparse neuronal activity, recurrent connections, and local lea…
COGITAO: A Visual Reasoning Framework To Study Compositionality & Generalization
Yassine Taoudi-Benchekroun, Klim Troyan, Pascal Sager +3
The ability to compose learned concepts and apply them in novel settings is key to human intelligence, but remains a persistent limitation in state-of-the-art machine learning mode…
A document is worth a structured record: Principled inductive bias design for document recognition
Benjamin Meyer, Lukas Tuggener, Sascha Hänzi +5
Many document types use intrinsic, convention-driven structures that serve to encode precise and structured information, such as the conventions governing engineering drawings. How…
Deep Retrieval at CheckThat! 2025: Identifying Scientific Papers from Implicit Social Media Mentions via Hybrid Retrieval and Re-Ranking
Pascal J. Sager, Ashwini Kamaraj, Benjamin F. Grewe +1
We present the methodology and results of the Deep Retrieval team for subtask 4b of the CLEF CheckThat! 2025 competition, which focuses on retrieving relevant scientific literature…
Learning Actionable World Models for Industrial Process Control
Peng Yan, Ahmed Abdulkadir, Gerrit A. Schatte +7
To go from (passive) process monitoring to active process control, an effective AI system must learn about the behavior of the complex system from very limited training data, formi…
The underlying structures of self-attention: symmetry, directionality, and emergent dynamics in Transformer training
Matteo Saponati, Pascal Sager, Pau Vilimelis Aceituno +2
Self-attention is essential to Transformer architectures, yet how information is embedded in the self-attention matrices and how different objective functions impact this process r…
A Comprehensive Survey of Agents for Computer Use: Foundations, Challenges, and Future Directions
Pascal J. Sager, Benjamin Meyer, Peng Yan +7
Agents for computer use (ACUs) are an emerging class of systems capable of executing complex tasks on digital devices -- such as desktops, mobile phones, and web platforms -- given…
Unsupervised Musical Object Discovery from Audio
Joonsu Gha, Vincent Herrmann, Benjamin Grewe +2
Current object-centric learning models such as the popular SlotAttention architecture allow for unsupervised visual scene decomposition. Our novel MusicSlots method adapts SlotAtte…