Full papers
Original research contributions with comprehensive analysis and evaluation.
Machine Learning/CORE Unranked
CAO 2026
Catch, Adapt, and Operate: Monitoring ML Models Under Drift Workshop
The CAO 2026 workshop is a specialized event affiliated with ICLR 2026, focused on advancing research in causal representation learning and its applications in artificial intelligence. It aims to bring together researchers to discuss theoretical foundations, novel methodologies, and practical applications of causal models in machine learning systems.
Key deadlines
Verified September 9, 2026Full paper
February 11, 2026
AoE
Workshop timeline
Submission and decisions
Full paperKey deadline
February 11, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Short papers
Concise presentations of promising ideas, preliminary results, or position papers.
Research areas in scope
01
Workshop Topics
Causal representation learningCausal inference in deep learningCausal structure discoveryCausal generalization and out-of-distribution robustnessCausal reinforcement learningCausal generative modelsCausal interpretability and explainabilityApplications of causal models in real-world domains
Policies worth checking twice
- Submissions must be anonymized for double-blind review.
- Papers must not be under review at any other conference or journal during submission.
- Accepted papers will be presented as oral or poster presentations at the workshop.
- Authors must submit a statement on the use of AI tools in the research and writing process.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026