Dear Researcher,
We invite you to submit your latest research to the Information Theory for Large Language Models (IT4LLM) workshop at ISIT2026, held July 3 in Guangzhou, China. As a researcher pushing the boundaries of intelligent systems, your work at the intersection of information theory and AI is exactly what we need to advance the next generation of efficient, reliable, and transparent language models.
Why Submit to IT4LLM?
• Elite Speaker Lineup: Present your work alongside keynotes from Prof. Yuejie Chi (Yale University) and Prof. Yingbin Liang (The Ohio State University).
• Cross-Disciplinary Panel: Engage with our distinguished panel including Prof. Deniz Gündüz (Imperial College London), Prof. Jiantao Jiao (UC Berkeley), and Prof. Ioannis Kontoyiannis (Cambridge University).
• Interdisciplinary Collaboration: Connect with researchers from information theory, machine learning, and NLP communities to tackle fundamental challenges in LLM efficiency and interpretability.
Our core topics include, but are not limited to:
• Information-theoretic analysis of LLM training and inference
• Efficient representation and compression for large-scale models
• Mutual information, rate-distortion, and capacity in language modeling
• Information bottleneck and feature learning in transformers
• Reliable and trustworthy AI through principled IT frameworks
• Evaluation metrics grounded in information theory
Submission Details:
• Deadline: April 7, 2026
• Notification: April 21, 2026
• Final Manuscripts: April 28, 2026
• Submission Link: https://edas.info/N34669
• Workshop Date: July 3, 2026 (Guangzhou, China)
• Website: https://niuxueyan.github.io/it4llm/
Whether you have a full research paper or a work-in-progress report, we would love to see your contribution in Guangzhou!

Best regards,
IT4LLM Organizers
• Dr. Xueyan Niu (Huawei Technologies)
• Prof. Jun Chen (McMaster University)
• Dr. Bo Bai (Huawei Technologies)