MMGR24@ACM-MM2024

About

MMGR Workshop

Welcome to 2^nd MMGR Workshop co-located with ACM Multimedia 2024!

Information generation (IG) and information retrieval (IR) are two key representative approaches of information acquisition, i.e., producing content either via generation or via retrieval. While traditional IG and IR have achieved great success within the scope of languages, the under-utilization of varied data sources in different modalities (i.e., text, images, audio, and video) would hinder IG and IR techniques from giving the full advances and thus limits the applications in the real world. Knowing the fact that our world is replete with multimedia information, this workshop encourages the development of deep multimodal learning for the research of IG and IR. Benefiting from a variety of data types and modalities, some latest prevailing techniques are extensively invented to show great facilitation in multimodal IG and IR learning, such as DALL-E, Stable Diffusion, GPT4, Sora, etc. Given the great potential shown by multimodal-empowered IG and IR, there can be still unsolved challenges and open questions in these directions. With this special issue, we aim to encourage more explorations in Deep Multimodal Generation and Retrieval, providing a platform for researchers to share insights and advancements in this rapidly evolving domain.

Calls

Call for Papers

In this workshop, we welcome three types of submissions:

Position or perspective papers (The same format & template as the main conference, but the manuscript’s length is limited to one of the two options: a) 4 pages plus 1-page reference; or b) 8 pages plus up to 2-page reference.): original ideas, perspectives, research vision, and open challenges in the topics of the workshop;
Featured papers (title and abstract of the paper, plus the original paper): already published papers or papers summarizing existing publications in leading conferences and high-impact journals that are relevant for the topics of the workshop;
Demonstration papers (up to 2 pages in length, plus unlimited pages for references): original or already published prototypes and operational evaluation approaches in the topics of the workshop.

All the accepted papers will be archived in the ACM MM proceedings. Authors of accepted papers will be presented at the workshop. Also, high-quality papers can be recommended to ACM ToMM Special Issue of MMGR.

We will select from the accepted papers the Best Paper Award, which will be announced during the workshop.

Topics and Themes

Topics of interests include but not limited to:

Multimodal Semantics Understanding, such as
- - Vision-Language Alignment Analysis
- - Multimodal Fusion and Embeddings
- - Large-scale Vision-Language Pre-training
- - Structured Vision-Language Learning
- - Visually Grounded Interaction of Language Modeling
- - Commonsense-aware Vision-Language Learning
- - Visually Grounded Language Parsing
- - Semantic-aware Vision-Language Discovery
- - Large Multimodal Models
Generative Models for Image/Video Synthesis, such as
- - Text-free/conditioned Image Synthesis
- - Text-free/conditioned Video Synthesis
- - Temporal Coherence in Video Generation
- - Image/Video Editing/Inpainting
- - Visual Style Transfer
- - Image/Video Dialogue
- - Panoramic Scene Generation
- - Multimodal Dialogue Response Generation
- - LLM-empowered Multimodal Generation
Multimodal Information Retrieval, such as
- - Image/Video-Text Compositional Retrieval
- - Image/Video Moment Retrieval
- - Image/Video Captioning
- - Image/Video Relation Detection
- - Image/Video Question Answering
- - Multimodal Retrieval with MLLMs
- - Hybrid Synthesis with Retrieval and Generation
Explainable and Reliable Multimodal Learning, such as

- Explainable Multimodal Retrieval
- Relieve Hallucination of LLMs
- Adversarial Attack and Defense
- Multimodal Learning for Social Good
- Multimodal-based Reasoning
- Multimodal Instruction Tuning
- Efficient Learning of MLLMs

Submission Instructions

Page limits include diagrams and appendices. Submissions should be written in English, and formatted according to the current ACM two-column conference format. Authors are responsible for anonymizing the submissions. Suitable LaTeX, Word, and Overleaf templates are available from the ACM Website (use “sigconf” proceedings template for LaTeX and the Interim Template for Word).

Review Process

All submissions will be peer-reviewed by at least two reviewers of experts in the field. The reviewing process will be two-way anonymized. Acceptance will be dependent on the relevance to the workshop topics, scientific novelty, and technical quality. The accepted workshop papers will be published in the ACM Digital Library.