This workshop aims to explore the potential of large language models to revolutionize the way we interact with multimodal information. A large language model is a type of artificial intelligence model designed to understand and generate natural language text. With the increasing amount of multimodal information such as audio, visual, and text data generated, there is a growing need of leveraging large generative language model for multimodal applications. Recently, a few notable multimodal models with a combination of large language models significantly enhanced their understanding and generate more accurate and nuanced responses. The workshop will provide an opportunity for researchers, practitioners, and industry professionals to explore the latest trends and best practices in the field of multimodal applications of large generative models. We also remark that the submissions are not limited to use such models.

Submission Guidelines

Submission Format: Submitted papers (.pdf format) must use the ACM Article Template https://www.acm.org/publications/proceedings-template. Please remember to add Concepts and Keywords.

Length: Submissions can be of varying length from 4 to 8 pages, plus additional pages for the reference pages; i.e., the reference page(s) are not counted to the page limit of 4 to 8 pages. There is no distinction between long and short papers, but the authors may themselves decide on the appropriate length of the paper. All papers will undergo the same review process and review period.

Reviewing Process: Paper submissions must conform with the "double-blind" review policy. All papers will be peer-reviewed by experts in the field. Acceptance will be based on relevance to the workshop, scientific novelty, and technical quality. The workshop papers will be published in the ACM Digital Library.

Committees

Organizing Committee

• Zheng Wang (Huawei Singapore Research Center, Singapore)
• Cheng Long (Nanyang Technological University, Singapore)
• Shihao Xu (Huawei Singapore Research Center, Singapore)
• Bingzheng Gan (Huawei Singapore Research Center, Singapore)
• Wei Shi (Huawei Singapore Research Center, Singapore)
• Zhao Cao (Huawei Technologies Co., Ltd, China)
• Tat-Seng Chua (National University of Singapore, Singapore)

Program committee

• TBA

Contact

All questions about submissions should be emailed to Zheng Wang (zheng011@e.ntu.edu.sg)