19.01.2026
MCML at AAAI 2026
15 Accepted Papers (12 Main, and 3 Workshops)
40th Conference on Artificial Intelligence, Singapore, Jan 20-27, 2026
We are happy to announce that MCML researchers have contributed a total of 15 papers to AAAI 2026: 12 Main, and 3 Workshop papers. Congrats to our researchers!
Main Track (12 papers)
B. Bühler • I. Bueno • E. Kasneci
Democratizing Writing Support with AI: Insights from One Year of Real-World Interactions with an Open-Access Writing Feedback Tool.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. GitHub
Democratizing Writing Support with AI: Insights from One Year of Real-World Interactions with an Open-Access Writing Feedback Tool.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. GitHub
H. Chen • J. Li • Y. Zhang • J. Bi • Y. Xia • J. Gu • V. Tresp
AUVIC: Adversarial Unlearning of Visual Concepts for Multi-modal Large Language Models.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
AUVIC: Adversarial Unlearning of Visual Concepts for Multi-modal Large Language Models.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
C. Fiedler
Statistical Learning Theory for Distributional Classification.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published.
Statistical Learning Theory for Distributional Classification.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published.
P. Hofman • Y. Sale • E. Hüllermeier
Uncertainty Quantification for Machine Learning: One Size Does Not Fit All.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
Uncertainty Quantification for Machine Learning: One Size Does Not Fit All.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
X. Jian • P. Zhang • L. Tian • F. Ji • W. Liang • W. P. Tay • B. Wen • F. Krahmer
Conformal Prediction for Multi-Source Detection on a Network.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
Conformal Prediction for Multi-Source Detection on a Network.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
Y. Lei • X. Ge • Y. Zhang • Y. Yang • B. Ma
Do Large Language Models Think Like the Brain? Sentence-Level Evidence from fMRI and Hierarchical Embeddings.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
Do Large Language Models Think Like the Brain? Sentence-Level Evidence from fMRI and Hierarchical Embeddings.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
G. D. Pelegrina • P. Kolpaczki • E. Hüllermeier
Shapley Value Approximation Based on k-Additive Games.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
Shapley Value Approximation Based on k-Additive Games.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
N. Walha • S. G. Gruber • T. Decker • Y. Yang • A. Javanmardi • E. Hüllermeier • F. Buettner
Fine-Grained Uncertainty Decomposition in Large Language Models: A Spectral Approach.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
Fine-Grained Uncertainty Decomposition in Large Language Models: A Spectral Approach.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
M. Wever • M. Muschalik • F. Fumagalli • M. Lindauer
HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
M. Wei • K. Yuan • S. Li • Y. Zhou • L. Bai • N. Navab • H. Ren • H. J. Lee • T. Vercauteren • N. Padoy
Where It Moves, It Matters: Referring Surgical Instrument Segmentation via Motion.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
Where It Moves, It Matters: Referring Surgical Instrument Segmentation via Motion.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
Y. Yeganeh • R. Xiao • G. Guvercin • N. Navab • A. Farshad
Conformable Convolution for Topologically Aware Learning of Complex Anatomical Structures.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
Conformable Convolution for Topologically Aware Learning of Complex Anatomical Structures.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv
W. Zhang • Q. Cheng • D. Skuddis • N. Zeller • D. Cremers • N. Haala
HI-SLAM2: Geometry-Aware Gaussian SLAM for Fast Monocular Scene Reconstruction.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv GitHub
HI-SLAM2: Geometry-Aware Gaussian SLAM for Fast Monocular Scene Reconstruction.
AAAI 2026 - 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv GitHub
Workshops (3 papers)
T. Decker • V. Tresp
Towards Quantifying Incompatibilities in Evaluation Metrics for Feature Attributions.
XAI4Science @AAAI 2026 - 2nd Workshop XAI4Science: From Understanding Model Behavior to Discovering New Scientific Knowledge at the 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. URL
Towards Quantifying Incompatibilities in Evaluation Metrics for Feature Attributions.
XAI4Science @AAAI 2026 - 2nd Workshop XAI4Science: From Understanding Model Behavior to Discovering New Scientific Knowledge at the 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. URL
X. Xue • X. Zhu
Towards Unified Vision Language Models for Forest Ecological Analysis in Earth Observation.
AI4ES @AAAI 2026 - Workshop on AI for Environmental Science at the 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv GitHub
Towards Unified Vision Language Models for Forest Ecological Analysis in Earth Observation.
AI4ES @AAAI 2026 - Workshop on AI for Environmental Science at the 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published. Preprint available. arXiv GitHub
Y. Zhang • S. Tang • Z. Li • Z. Han • V. Tresp
WebArbiter: A Principle-Guided Reasoning Process Reward Model for Web Agents.
LaMAS @AAAI 2026 - Workshop on LLM-based Multi-Agent Systems: Towards Responsible, Reliable, and Scalable Agentic Systems at the 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published.
WebArbiter: A Principle-Guided Reasoning Process Reward Model for Web Agents.
LaMAS @AAAI 2026 - Workshop on LLM-based Multi-Agent Systems: Towards Responsible, Reliable, and Scalable Agentic Systems at the 40th Conference on Artificial Intelligence. Singapore, Jan 20-27, 2026. To be published.
Related
05.02.2026
Needle in a Haystack: Finding Exact Moments in Long Videos
ECCV 2024 research introduces RGNet, an AI model that finds exact moments in long videos using unified retrieval and grounding.
04.02.2026
Benjamin Busam Leads Design of Bavarian Earth Observation Satellite Network “CuBy”
Benjamin Busam leads the scientific design of the “CuBy” satellite network, delivering AI-ready Earth observation data for Bavaria.
©Florian Generotzky / LMU
30.01.2026
Cracks in the Foundations of Cosmology
Daniel Grün examines cosmological tensions that challenge the Standard Model and may point toward new physics.
