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2026 International Conference on Machine Learning and Large Models(ICMLM 2026) will be held in Chengdu from March 6th to March 8th, 2026. The conference will focus on cutting-edge fields such as wireless communication, 5G/6G, the Internet of Things, network security, encryption technologies, and blockchain. It aims to promote innovation in communication technology and data security, build a platform for academic and industry exchange, and foster cross-disciplinary collaboration and technological advancement. We sincerely invite experts and scholars worldwide to submit original papers, share the latest research findings, and jointly discuss industry hotspots and challenges. The conference will feature keynote speeches, oral presentations, interactive sessions, and more. We look forward to your active participation. Researchers, engineers, and professionals from all sectors are warmly welcomed to submit papers and register to attend this grand event, together creating a new future for secure communication in the digital era!

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CFP

Full Paper Submission Date

October 10, 2025

Registration Deadline

February 1, 2026

Final Paper Submission Date

February 5, 2026

Conference Dates

March 20-22, 2026

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Call For Papers

·Machine learning,

· Deep learning

· Neural networks

· ...

·Large Model Technologies

·Generative Large Models

·Pre-trained Language Models

· ...

·Application Practices of Machine Learning and Large Models

·Natural Language Processing

·Computer Vision

· ...

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Publication

Publication

Submitted paper will be peer reviewed by conference committees, and accepted papers after registration and presentation will be published in the Conference Proceedings, which will be submitted for indexing by Ei Compendex, Scopus.

Note: All submitted articles should report original results, experimental or theoretical, not previously published or being under consideration for publication elsewhere. Articles submitted to the conference should meet these criteria. We firmly believe that ethical conduct is the most essential virtue of any academic. Hence, any act of plagiarism or other misconduct is totally unacceptable and cannot be tolerated.

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