Call for Papers

We invite submissions on any aspect of generalizing from limited resources in the open world. Considering the recent significant success of large model, in this year, we will include more generalization approaches in openworld for generative AI models. We welcome research contributions related to the following (but not limited to) topics:
  • New methods for in-context learning
  • Applications of large AI models in vertical domains
  • New methods for AI alignment
  • New methods and benchmarks of open set/world learning problem
  • New methods for few-/zero-shot learning
  • New methods for domain-adaptation methods
  • New methods for training generative models under limited data
  • Benchmark for evaluating model generalization
  • Understanding the generalization vulnerabilities of deep learning systems
  • Network sparsity, quantization, distillation, etc.
  • Neural architecture search (NAS)
  • Efficient network architecture design
  • Efficient methods for generative models like diffusion, large language models
  • Hardware implementation and on-device deployment
  • On-device learning
  • Brain-inspired artificial intelligence like spiking neural networks (SNN)
  • Optimization on parallel and distributed training
Submission Format: Submissions need to be anonymized and follow Springer's guidelines and author instructions. The workshop considers two types of submissions: (1) Full Paper: Papers are limited to 12-15 pages; (2) Short Paper: Papers are limited to 6-11 pages.
Peer review: Paper submissions must conform with the “double-blind” review policy. All papers will be peer-reviewed by experts in the field, they will receive at least two reviews. Based on the area chair recommendations, the accepted papers will be allocated either a contributed talk or a poster presentation.
Important: The accepted papers will be published on the proceeding of Communications in Computer and Information Science, indexed in EI-Compendex, etc.
Submission Site:
Submission Due: 19th May, 2024 AoE

Workshop Schedule


Jinyang Guo

Beihang University

Yuqing Ma

Beihang University

Ruihao Gong

SenseTime Research

Ning Liu

Midea Group

Associate Organizer

Olivera Kotevska

Oak Ridge National Laboratory

Shanghang Zhang

Peking University

Pengfei Liu

Shanghai Jiaotong University

Advisory Board

Xianglong Liu

Beihang University

Rogerio Schmidt Feris

MIT-IBM Watson AI lab

Publication Chairs

Changyi He

Beihang University

Ge Yang

Beihang University

Publicity Chairs

Xingyu Zheng

Beihang University

Local Arrangement Chairs

Yifu Ding

Beihang University