Call for Papers
Recent advances in machine learning and artificial intelligence have brought compression back to the forefront of information science. Once regarded primarily as a tool for efficient data storage and transmission, compression has now emerged as a unifying principle linking representation learning, generalization, and efficient communication. This workshop explores how classical information-theoretic concepts—such as the rate–distortion tradeoff, minimum description length, and universal compression—are being reimagined and extended in modern contexts like neural source coding, model compression, semantic communication, and generative AI. It aims to foster dialogue between information theorists and machine learning researchers to examine how compression not only enables efficient inference and transmission but also offers a powerful lens for explaining and designing intelligent systems.
The program will feature invited talks, contributed presentations, and panel discussions that bridge theory and practice, laying the groundwork for the next generation of compression-inspired learning and communication paradigms.
Topics of interest include, but are not limited to:
- Theoretical foundations and practical methods for neural source coding and generative compression
- Task-, context-, and semantic-aware compression
- Model compression and efficient representation for neural networks and emerging data modalities
- Compression-inspired approaches to prediction, inference, and representation learning
All accepted papers will be presented as posters during the poster session. We welcome all relevant recent submissions that have been presented, published or are currently undergoing review elsewhere, if the authors decide not to publish their full-paper on IEEE Xplore. Some papers will also be selected for spotlight presentations.
Important Dates
- Submission of Workshop Papers: April 7, 2026 (11:59 PM, anywhere in the world!)
- Notification of Acceptance: April 21, 2026
- Final Manuscripts: April 28, 2026
- Workshop Date: July 3, 2026
Submission Details
Submissions are now open on EDAS!
Prospective authors should prepare their papers in accordance with the regular submission guidelines of the 2026 IEEE International Symposium on Information Theory (https://2026.ieee-isit.org/information-authors).
Each paper will go through a rigorous review process. The workshop will follow a single-blind reviewing policy, aligned with the ISIT 2025, which means that the all submitted manuscripts should include author names and affiliations. The authors can post their papers on arXiv if they wish to do so.
We will offer authors the choice to publish their accepted papers on IEEE Xplore.
We welcome all relevant submissions that have been presented, published or are currently undergoing review elsewhere, if the authors decide not to publish their full-paper on IEEE Xplore.
An author of an accepted paper must register to the workshop and present a poster. For some selected papers, there will be a spotlight presentation. To maintain the interactive nature of the workshop, we kindly request all presentations to be in-person.
Only accepted papers that are presented will be published on IEEE Xplore. The requirements of the poster will be communicated with the acceptance notification for the paper.