10 citations · 18 across the 13 of their papers we have counts for
14 papers
Muffin - A Shared Memory Buffer for Asynchronous AI Agents
Ping-Lin Kuo, Suman Navaratnarajah, Christian Frey +2
The rise of Agentic AI systems has changed the landscape of artificial intelligence by enabling strong reasoning capabilities through specialized multi-agent interaction with struc…
ValueGround: Evaluating Culture-Conditioned Visual Value Grounding in MLLMs
Zhipin Wang, Christoph Leiter, Christian Frey +3
Cultural values are expressed not only through language but also through visual scenes and everyday social practices. Yet existing evaluations of cultural values in language models…
Learning to Order: Task Sequencing as In-Context Optimization
Jan Kobiolka, Christian Frey, Arlind Kadra +2
Task sequencing (TS) is one of the core open problems in Deep Learning, arising in a plethora of real-world domains, from robotic assembly lines to autonomous driving. Unfortunatel…
POP: Prior-Fitted First-Order Optimization Policies
Jan Kobiolka, Christian Frey, Gresa Shala +3
Gradient-based optimizers are highly sensitive to design choices in their adaptive learning rate mechanisms. To address this limitation, we introduce POP, a meta-learned Reinforcem…
End-to-End Compression for Tabular Foundation Models
Guri Zabërgja, Rafiq Kamel, Arlind Kadra +2
The long-standing dominance of gradient-boosted decision trees for tabular data has recently been challenged by in-context learning tabular foundation models. In-context learning m…
Towards Reproducibility in Predictive Process Mining: SPICE -- A Deep Learning Library
Oliver Stritzel, Nick Hühnerbein, Simon Rauch +5
In recent years, Predictive Process Mining (PPM) techniques based on artificial neural networks have evolved as a method for monitoring the future behavior of unfolding business pr…
Zhyper: Factorized Hypernetworks for Conditioned LLM Fine-Tuning
M. H. I. Abdalla, Zhipin Wang, Christian Frey +2
Large Language Model (LLM) conditioning refers to instructing an LLM to generate content in accordance with the norms and values of a specific culture, beliefs of a particular poli…
SHAining on Process Mining: Explaining Event Log Characteristics Impact on Algorithms
Andrea Maldonado, Christian M. M. Frey, Sai Anirudh Aryasomayajula +3
Process mining aims to extract and analyze insights from event logs, yet algorithm metric results vary widely depending on structural event log characteristics. Existing work often…
Tabular Data: Is Deep Learning all you need?
Guri Zabërgja, Arlind Kadra, Christian M. M. Frey +1
Tabular data represent one of the most prevalent data formats in applied machine learning, largely because they accommodate a broad spectrum of real-world problems. Existing litera…
DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification
Sandra Gilhuber, Julian Busch, Daniel Rotthues +2
Node classification is one of the core tasks on attributed graphs, but successful graph learning solutions require sufficiently labeled data. To keep annotation costs low, active g…
V-Coder: Adaptive AutoEncoder for Semantic Disclosure in Knowledge Graphs
Christian M. M. Frey, Matthias Schubert
Semantic Web or Knowledge Graphs (KG) emerged to one of the most important information source for intelligent systems requiring access to structured knowledge. One of the major cha…
SEA: Graph Shell Attention in Graph Neural Networks
Christian M. M. Frey, Yunpu Ma, Matthias Schubert
A common issue in Graph Neural Networks (GNNs) is known as over-smoothing. By increasing the number of iterations within the message-passing of GNNs, the nodes' representations of…
APPTeK: Agent-Based Predicate Prediction in Temporal Knowledge Graphs
Christian M. M. Frey, Yunpu Ma, Matthias Schubert
In temporal Knowledge Graphs (tKGs), the temporal dimension is attached to facts in a knowledge base resulting in quadruples between entities such as (Nintendo, released, Super Mar…
Efficient Information Flow Maximization in Probabilistic Graphs
Christian Frey, Andreas Züfle, Tobias Emrich +1
Reliable propagation of information through large networks, e.g., communication networks, social networks or sensor networks is very important in many applications concerning marke…