Multimodal Algorithmic Reasoning Workshop (MAR-CVPR 2026) Call for Papers

Multimodal Algorithmic Reasoning Workshop (MAR-CVPR 2026)

June 3rd / 4th, 2026, Denver

Held in conjunction with CVPR 2026

https://marworkshop.github.io/cvpr26/


CALL FOR CONTRIBUTIONS

Large AI frameworks have been rapidly increasing their data modeling
capabilities in recent years, with compelling applications emerging
frequently, some of which may even appear to challenge human
intelligence. Yet, despite this impressive performance, there remain
open questions about whether these models possess the foundations of
general intelligence, or whether they succeed without human-like
understanding. This motivates the development of better tools for
assessing such models, alongside continued advances in model design.

This workshop focuses on multimodal algorithmic reasoning, where an
agent must assimilate information from multiple modalities for complex
problem solving. Real-world examples of such problems include: (i)
chain-of-thought reasoning across modalities, (ii) vision-and-language
problem solving, (iii) agentic reasoning and tool use, and (iv)
reasoning under physical constraints, among others. Over the past
year, we have seen rapid advances in AI that more effectively bridge
modalities, inspiring both optimism about superhuman capabilities and
skepticism about the limits of current approaches. This is an
opportune moment to explore critical challenges, including new
architectures for visual and physical reasoning, data generation via
simulators, and the theoretical limits of reasoning in large models.

Through talks by outstanding researchers and faculty, we aim to delve
deeply into this topic at the intersection of multimodality,
algorithmic foundations, and cognitive science, to better understand
what has been achieved in machine intelligence and what remains
missing relative to human cognition, as we seek the next rungs on the
ladder toward advancing AI to the next frontier.

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IMPORTANT DATES & DETAILS

Submission deadline: February 27 (Anywhere on Earth)  

Final decision notification: March 20 

Camera Ready: April 10

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TOPICS 

We invite submissions of original and high-quality research papers in
the topics related to multimodal algorithmic reasoning. The topics for
MAR-CVPR 2026 include, but are not limited to:

* Multimodal structured and multi-step reasoning across vision,
language, audio, and other modalities, including compositional and
programmatic inference.

* Multimodal foundation models and world models for reasoning,
planning, and decision-making, and their connections to general
intelligence.

* Reasoning under physical, geometric, and causal constraints,
including embodied agents, simulators, and digital twins.

* Multi-agent reasoning and collaboration, including debate,
coordination, mixture-of-experts, and reward- or critique-based
aggregation.

* Extreme generalization and concept learning, including few-shot,
zero-shot, and out-of-distribution multimodal reasoning.

* Scaling laws, efficiency, and test-time reasoning, including
inference-time optimization, self-refinement, and tool-augmented
reasoning.

* Benchmarks, datasets, diagnostics, and evaluation, including
synthetic data, interpretability, and systematic analysis of
shortcomings and failure modes in multimodal AI models.

* Theoretical and cognitive perspectives on multimodal reasoning,
including limits of current models and insights from human cognition.

* Human–AI reasoning comparisons and foundations, including
perspectives from psychology, neuroscience, and child development;
theoretical limits of reasoning in large models; and position papers
on how current multimodal AI reasoning differs from human cognition.

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SUBMISSION INSTRUCTIONS

We are inviting submissions of both original and previously published works.  

* All submissions are handled via the workshop's OpenReview
website:
https://openreview.net/group?id=thecvf.com/CVPR/2026/Workshop/MAR.

* Submissions should be made in PDF format and must follow the CVPR
2026 submission style provided here:
https://github.com/cvpr-org/author-kit/archive/refs/tags/CVPR2026-v1(latex).zip.

* We allow three types of submissions:

     1. Original and unpublished papers of up to 8 pages, which will
     be published as part of the CVPR 2026 workshop proceedings and
     will be released on the workshop website upon acceptance

     2. Original and unpublished papers of up to 4 pages, which will
     not be included in the CVPR workshop proceedings and will be
     released only on the workshop website upon acceptance; and

    3. Previously accepted or published papers of up to 8 pages, which
    will be released only on the workshop website upon acceptance to
    our workshop.

* All the page limits above are excluding references,
acknowledgements, and other non-technical content (e.g., scope,
limitations, impact statement).

* Authors may upload an optional Appendix, containing additional
details, proofs, images, etc. as part of the submission pdf (after the
references) or in a separate zip file (with a max of 50MB in
size). The deadline for submitting these supplementary materials is
the same as that for the main paper.

* All submissions should maintain author anonymity and should abide by
the CVPR 2026 conference guidelines for double-blind review.

* Accepted papers will be presented as either an oral, spotlight, or
poster presentation. At least one author of each accepted submission
must present the paper at the workshop in-person.

* Presentation of accepted papers at our workshop will follow the same
policy as that for accepted papers at the CVPR 2026 main conference.

* Accepted papers will be made publicly accessible on the workshop
website shortly after the camera-ready deadline.

* The submitting authors are expected to also be reviewers for the
workshop.

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WORKSHOP ORGANIZERS

Anoop Cherian, Mitsubishi Electric Research Laboratories

Suhas Lohit, Mitsubishi Electric Research Laboratories

Kuan-Chuan Peng, Mitsubishi Electric Research Laboratories

Honglu Zhou, Salesforce AI Research

Kevin A. Smith, Massachusetts Institute of Technology

Joshua B. Tenenbaum, Massachusetts Institute of Technology

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CONTACT

Email: smart101@googlegroups.com 

Website: https://marworkshop.github.io/cvpr26/