David Berghaus

According to our database, David Berghaus authored at least 23 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

EVIL: Evolving Interpretable Algorithms for Zero-Shot Inference on Event Sequences and Time Series with LLMs.

David Berghaus

CoRR, April, 2026

Adaptive Loops and Memory in Transformers: Think Harder or Know More?

Markus Frey, Behzad Shomali, Ali Hamza Bashir, David Berghaus, Joachim Köhler, Mehdi Ali

CoRR, March, 2026

Is continuous CoT better suited for multi-lingual reasoning?

Ali Hamza Bashir, Behzad Shomali, Markus Frey, Mehdi Ali, Rafet Sifa, David Berghaus

CoRR, March, 2026

Beyond Reinforcement Learning: Fast and Scalable Quantum Circuit Synthesis.

Lukas Theißinger, Thore Gerlach, David Berghaus, Christian Bauckhage

CoRR, February, 2026

Foundation Inference Models for Ordinary Differential Equations.

Maximilian Mauel, Johannes R. Hübers, David Berghaus, Patrick Seifner, Ramsés J. Sánchez

CoRR, February, 2026

Domain-Adaptation through Synthetic Data: Fine-Tuning Large Language Models for German Law.

Ali Hamza Bashir, Muhammad Rehan Khalid, Kostadin Cvejoski, Jana Birr, Jule Berghaus, Armin Berger, Sandra Halscheidt, Christian Temath, Rafet Sifa, David Berghaus

CoRR, January, 2026

2025

Towards Foundation Inference Models that Learn ODEs In-Context.

Maximilian Mauel, Manuel Hinz, Patrick Seifner, David Berghaus, Ramsés J. Sánchez

CoRR, October, 2025

On Foundation Models for Temporal Point Processes to Accelerate Scientific Discovery.

David Berghaus, Patrick Seifner, Kostadin Cvejoski, Ramsés J. Sánchez

CoRR, October, 2025

Towards Fast Coarse-graining and Equation Discovery with Foundation Inference Models.

Manuel Hinz, Maximilian Mauel, Patrick Seifner, David Berghaus, Kostadin Cvejoski, Ramsés J. Sánchez

CoRR, October, 2025

In-Context Learning of Temporal Point Processes with Foundation Inference Models.

David Berghaus, Patrick Seifner, Kostadin Cvejoski, César Ojeda, Ramsés J. Sánchez

CoRR, September, 2025

Reasoning LLMs in the Medical Domain: A Literature Survey.

Armin Berger, Sarthak Khanna, David Berghaus, Rafet Sifa

CoRR, August, 2025

Foundation Inference Models for Stochastic Differential Equations: A Transformer-based Approach for Zero-shot Function Estimation.

Patrick Seifner, Kostadin Cvejoski, David Berghaus, César Ojeda, Ramsés J. Sánchez

CoRR, February, 2025

Towards Unified Multimodal Financial Forecasting: Integrating Sentiment Embeddings and Market Indicators via Cross-Modal Attention.

Sarthak Khanna, Armin Berger, David Berghaus, Tobias Deußer, Lorenz Sparrenberg, Rafet Sifa

Proceedings of the 12th IEEE International Conference on Data Science and Advanced Analytics, 2025

Reasoning LLMs in the Medical Domain: A Literature Survey.

Armin Berger, Sarthak Khanna, Lorenz Sparrenberg, Tobias Deußer, David Berghaus, Rafet Sifa

Proceedings of the 12th IEEE International Conference on Data Science and Advanced Analytics, 2025

History Rhymes: Macro-Contextual Retrieval for Robust Financial Forecasting.

Sarthak Khanna, Armin Berger, Muskaan Chopra, David Berghaus, Rafet Sifa

Proceedings of the IEEE International Conference on Big Data, 2025

Multi-Modal Vision vs. Text-Based Parsing: Benchmarking LLM Strategies for Invoice Processing.

David Berghaus, Armin Berger, Lars Hillebrand, Kostadin Cvejoski, Rafet Sifa

Proceedings of the IEEE International Conference on Big Data, 2025

2024

Computation of Laplacian eigenvalues of two-dimensional shapes with dihedral symmetry.

David Berghaus, Robert Stephen Jones, Hartmut Monien, Danylo V. Radchenko

Adv. Comput. Math., June, 2024

Foundation Inference Models for Markov Jump Processes.

David Berghaus, Kostadin Cvejoski, Patrick Seifner, César Ali Marin Ojeda, Ramsés J. Sánchez

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Advancing Risk and Quality Assurance: A RAG Chatbot for Improved Regulatory Compliance.

Lars Hillebrand, Armin Berger, Daniel Uedelhoven, David Berghaus, Ulrich Warning, Tim Dilmaghani Khameneh, Bernd Kliem, Thomas Schmid, Rüdiger Loitz, Rafet Sifa

Proceedings of the IEEE International Conference on Big Data, 2024

Optimizing Rare Disease Patient Matching with Large Language Models.

Armin Berger, Ali Hamza Bashir, David Berghaus, Mowmita, Nazia Afsan, Lorenz Grigull, Lara Fendrich, Henriette Högl, Gundula Ernst, Ralf Schmidt, David Bascom, Tom Anglim Lagones, Tobias Deußer, Thiago Bell, Max Lübbering, Rafet Sifa

Proceedings of the IEEE International Conference on Big Data, 2024

Advancing Personalized Medicine: A Scalable LLM-based Recommender System for Patient Matching.

Armin Berger, David Berghaus, Ali Hamza Bashir, Lorenz Grigull, Lara Fendrich, Tom Anglim Lagones, Henriette Högl, Gundula Ernst, Ralf Schmidt, David Bascom, Tobias Deußer, Thiago Bell, Max Lübbering, Rafet Sifa

Proceedings of the IEEE International Conference on Big Data, 2024

Fine-Tuning Large Language Models for Compliance Checks.

Thiago Bell, David Leonhard, Ali Hamza Bashir, Tim Dilmaghani Khameneh, Mohamed Khaled, Ulrich Warning, Rüdiger Loitz, Sandra Halscheidt, Jana Birr, Armin Berger, Rafet Sifa, David Berghaus

Proceedings of the IEEE International Conference on Big Data, 2024

2023

On the computation of modular forms on noncongruence subgroups.

David Berghaus, Hartmut Monien, Danylo V. Radchenko

Math. Comput., October, 2023