About

MMGR Workshop

Welcome to 3rd MMGR Workshop co-located with ACM Multimedia 2025!

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, video, touch, 3D point cloud, EEG signals, and more) 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 special issue 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 workshop, 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:

  1. 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;
  2. 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;
  3. 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
  • Multimodal LLM, such as
    • - Multimodal Foundation Model
    • - Continue Learning for Multimodal LLM
    • - Unified Architectures for Multimodal LLM
    • - Vision-Language Reasoning and Chain-of-thought
    • - Retrieval-augmented Multimodal LLMs
    • - Parameter-efficient Adaptation and Fine-tuning
    • - Multi-agent and Compositional Approaches
    • - Safety, Fairness and Hallucination in Multimodal LLMs
    • - Evaluation Protocols and Benchmarks

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.


Important Dates

  • Paper Submission: July 11, 2025 (AoE)
  • Notification of Acceptance: August 1, 2025 (AoE)
  • Camera-ready Submission: August 11, 2025 (AoE) [Firm Deadline]
  • Workshop dates: 28 October, 2025 (AoE)

Papers

Accepted Papers

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  1. DSS:Implicit Representation-Based Face Restoration with Diffusion Prior
    Gang He, YingFu Zhang, SiqiWang, Kepeng Xu
  2. Beyond Nearest Neighbors: Semantic Compression and Graph-Augmented Retrieval for Enhanced Vector Search
    Rahul Raja, Arpita Vats
  3. StgcDiff: Spatial-Temporal Graph Condition Diffusion for Sign Language Transition Generation
    Jiashu He, Jiayi He, Shengeng Tang, Huixia Ben, Lechao Cheng, Richang Hong
  4. AMR-CSI: Adaptive Multimodal RAG for Cold Start Indexing
    Siva Prasad, Shreya Saxena, Mukkamala Venkata Sai Prakash, Zishan Ahmad, Vishal Vaddina
  5. LViCAR: Diffusion Models for Perceptual Quality Enhancement in Video Compression Artifact Reduction
    Shiv Gehlot, Guan-Ming Su
  6. Prospective Analysis of Semantic Image Retrieval: Comparing Scene Graph, Visual Features, and Captions
    Takahiro Komamizu
  7. Mamba-Based Multimodal Continual Learning for Audio-Visual Classification with Prototype-Enhanced Anti-Forgetting Mechanism
    Jingyang Lin, Xinru Ying, Jiaqi Mo, Lina Wei, Fangfang Wang, Canghong Jin, Guanlin Chen
  8. RenderTXT: High-Fidelity Text Rendering in Images with LLM
    Shengqiong Wu, Bobo Li, Meishan Zhang, Jun Yu, Min Zhang, Tat-Seng Chua

Workshop Schedule

Program

Date: October 28, 2025.


TBD   |   An opening of the workshop
TBD   |   Keynote 1:
TBD   |   Keynote 2:
TBD   |   Coffee Break
TBD   |   Round Table Discussion, by Workshop Host
TBD   |   Keynote 3:
TBD   |   Keynote 4:
TBD   |   Presentation 1
TBD   |   Presentation 2
TBD   |   Presentation 3
TBD   |   Workshop Closing

Talks

Invited Speakers

Organization

Workshop Organizers

Wei Ji

National University of Singapore

Hong Liu

Osaka University

Lizi Liao

Singapore Management University

Yuchong Sun

Renmin University

Yadan Luo

University of Queensland

Xin Wang

Tsinghua University

Shin'ichi Satoh

National Institute of Informatics

Contact

Contact us

Join and post at our Google Group!
Email the organziers at mmgr25@googlegroups.com .