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We are excited to announce the CVPR 2026 Workshop on Trustworthy, Robust, Uncertainty-Aware, and Explainable Visual Intelligence and Beyond (TRUE-V), which will be held in Denver, Colorado, USA on June 3 or 4, 2026.
Modern vision and vision-language systems are increasingly deployed in safety-critical and real-world settings, yet they remain opaque, brittle, and difficult to calibrate. TRUE-V aims to advance principled foundations and practical methodologies for trustworthy visual intelligence, spanning interpretability, robustness, uncertainty, alignment, and responsible deployment.
We welcome theoretical, methodological, and applied contributions that push forward the science and practice of trustworthy AI in vision and beyond. The topics of interest includes aspects that can help to advance Trustworthy Visual Intelligence, including (but not limited to):
• Interpretable and explainable computer vision
• Robustness and reliability under distribution shift
• Uncertainty estimation and trust calibration
• Concept bottleneck & modular architectures
• Alignment, safety, and ethical considerations in vision models
• Human-in-the-loop evaluation and Evaluation benchmarks
• Trustworthy deployment in high-stakes domains
• Vision-language and multimodal reasoning under uncertainty
Submission are now open through OpenReview at:
https://openreview.net/group?
We welcome and encourage the authors to consult the submission guidelines and important dates listed on the workshop website: https://trustworthy-
The paper submission deadline is Mar 20, 2026 at 23:59 AoE. Accepted papers will be presented as posters, with a subset selected for spotlight talks. Please feel free to reach out to the organizers directly if you have any questions.
We welcome your submissions and look forward to your contributions! Please feel free to forward this CFP to your networks.
This workshop is organized by:
– Lily Weng (UC San Diego, lweng@ucsd.edu),
– Nghia Hoang (Washington State University, trongnghia.hoang@
– Tammy Riklin Raviv (Ben Gurion University, rrtammy@bgu.ac.il)
– Giuseppe Raffa (Intel Labs, giuseppe.raffa@intel.com
– Arno Blaas (Apple, ablaas@apple.com)
– Eunji Kim (Amazon, kce407@snu.ac.kr)
– Bhavya Kailkhura (LLNL, kailkhura1@llnl.gov)
– Kowshik Thopalli (LLNL, thopalli1@llnl.gov)