Kajetan Schweighofer

According to our database, Kajetan Schweighofer authored at least 18 papers between 2021 and 2026.

Collaborative distances:

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

2026

Overcoming Forgetting in LLM Fine-Tuning with Evolution Strategies.

Kajetan Schweighofer, Conor F. Hayes, Roberto Dailey, Risto Miikkulainen, Xin Qiu

CoRR, May, 2026

Efficient Pre-Training of LLMs through Truncated SVD Layers.

Kaivan Kamali, Kajetan Schweighofer, Hormoz Shahrzad, Olivier Francon, Babak Hodjat, Risto Miikkulainen

CoRR, May, 2026

Position: agentic AI orchestration should be Bayes-consistent.

Theodore Papamarkou, Pierre Alquier, Matthias Bauer, Wray L. Buntine, Andrew Davison, Gintare Karolina Dziugaite, Maurizio Filippone, Andrew Y. K. Foong, Vincent Fortuin, Dimitris Fouskakis, Jes Frellsen, Eyke Hüllermeier, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Nikita Kotelevskii, Salem Lahlou, Yingzhen Li, Fang Liu, Clare Lyle, Thomas Möllenhoff, Konstantina Palla, Maxim Panov, Yusuf Sale, Kajetan Schweighofer, Artem Shelmanov, Siddharth Swaroop, Martin Trapp, Willem Waegeman, Andrew Gordon Wilson, Alexey Zaytsev

CoRR, May, 2026

ImageSet2Text: Describing Sets of Images Through Text.

Piera Riccio, Francesco Galati, Kajetan Schweighofer, Noa Garcia, Nuria Oliver

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Addressing Pitfalls in the Evaluation of Uncertainty Estimation Methods for Natural Language Generation.

Mykyta Ielanskyi, Kajetan Schweighofer, Lukas Aichberger, Sepp Hochreiter

CoRR, October, 2025

xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity.

Maximilian Beck, Kajetan Schweighofer, Sebastian Böck, Sebastian Lehner, Sepp Hochreiter

CoRR, October, 2025

Uncertainty Quantification for Regression using Proper Scoring Rules.

Alexander Fishkov, Kajetan Schweighofer, Mykyta Ielanskyi, Nikita Kotelevskii, Mohsen Guizani, Maxim Panov

CoRR, September, 2025

Safe and Certifiable AI Systems: Concepts, Challenges, and Lessons Learned.

Kajetan Schweighofer, Barbara Brune, Lukas Gruber, Simon Schmid, Alexander Aufreiter, Andreas Gruber, Thomas Doms, Sebastian Eder, Florian Mayer, Xaver-Paul Stadlbauer, Christoph Schwald, Werner Zellinger, Bernhard Nessler, Sepp Hochreiter

CoRR, September, 2025

Combining Bayesian and Evidential Uncertainty Quantification for Improved Bioactivity Modeling.

Bola Khalil, Kajetan Schweighofer, Natalia Dyubankova, Gerard J. P. van Westen, Herman van Vlijmen

J. Chem. Inf. Model., 2025

On Information-Theoretic Measures of Predictive Uncertainty.

Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

The Disparate Benefits of Deep Ensembles.

Kajetan Schweighofer, Adrián Arnaiz-Rodríguez, Sepp Hochreiter, Nuria Oliver

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Improving Uncertainty Estimation through Semantically Diverse Language Generation.

Lukas Aichberger, Kajetan Schweighofer, Mykyta Ielanskyi, Sepp Hochreiter

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Rethinking Uncertainty Estimation in Natural Language Generation.

Lukas Aichberger, Kajetan Schweighofer, Sepp Hochreiter

CoRR, 2024

Semantically Diverse Language Generation for Uncertainty Estimation in Language Models.

Lukas Aichberger, Kajetan Schweighofer, Mykyta Ielanskyi, Sepp Hochreiter

CoRR, 2024

2023

Introducing an Improved Information-Theoretic Measure of Predictive Uncertainty.

Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Sepp Hochreiter

CoRR, 2023

Quantification of Uncertainty with Adversarial Models.

Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Günter Klambauer, Sepp Hochreiter

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

A Dataset Perspective on Offline Reinforcement Learning.

Kajetan Schweighofer, Marius-Constantin Dinu, Andreas Radler, Markus Hofmarcher, Vihang Prakash Patil, Angela Bitto-Nemling, Hamid Eghbal-zadeh, Sepp Hochreiter

Proceedings of the Conference on Lifelong Learning Agents, 2022

2021

Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning.

Kajetan Schweighofer, Markus Hofmarcher, Marius-Constantin Dinu, Philipp Renz, Angela Bitto-Nemling, Vihang Patil, Sepp Hochreiter

CoRR, 2021