会议信息

AIFM 2026: International Conference on Artificial Intelligence and Foundation Model

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AIFM
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截稿日期:
2026-04-23
通知日期:
2026-05-28
会议日期:
2026-06-26
会议地点:
Urumqi, China
届数:
2
浏览: 6470   关注: 1   参加: 0

会伴指数 (CP-I)

41.1 / 100
全站第 4,789 名 / 共 5,682 个会议 · 前 85%

人工智能与机器学习 第 607 / 739

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
30
社区关注 (10%)
24
资料公开度 (15%)
35

用到的输入: 有据可查的届次：2 · 在会伴关注它的研究者：1 人 · 过去 24 个月打开过本页的研究者：9 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-15

征稿

AIFM 2026 (International Conference on Artificial Intelligence and Foundation Model) is an academic conference held in Urumqi, China on 2026-06-26. The paper submission deadline is 2026-04-23. Acceptance notifications are sent on 2026-05-28.

2026 2nd International Conference on Artificial Intelligence and Foundation Model (AIFM 2026) will be held from June 26-28 2026 in Urumqi, China. This conference is an important academic event in the global field of artificial intelligence, aiming to gather experts and scholars from academia, industry, and government agencies around the world to jointly explore the latest developments and future directions of artificial intelligence and its large-scale model technology.All papers, both invited and contributed, will be reviewed by two or three expert reviewers from the conference committees. After a careful reviewing process, all accepted papers of AIFM 2026 will be published in ACM International Conference Proceedings Series, which will be archived in the ACM Digital Library, and indexed by EI Compendex, Scopus. The topics of interest for submission include, but are not limited to: Track 1: Theoretical Foundations of Foundation Model Basic model framework Model training and optimization Distributed computing High performance computing optimization Data management and efficient access Large model compilation optimization Multimodal fusion Reinforcement learning Pre-training Track 2： Model Security and Large-scale Intelligence Counter attack and defense Data security and privacy protection Model inversion attack Model stealing attack Data extraction attack Attack detection Outlier detection Acting exercise Federated learning Generating model security Track 3： Foundation Model Applications Image classification and object detection Image generation and editing Multimodal understanding Depth reasoning Urban computing Spatio-temporal data mining Natural language processing Visual language model Track 4： Embodied Intelligence and Robotics Intelligent robot Visual tracking Machine translation Robot perception Path planning Task planning and intelligent control Robot system More related topics...
由 Dou Sun 最后更新于

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