Topic

Paper Submission

2027 International Conference on Artificial Intelligence and Generation Technologies (AIGT 2027), to be held from May 14 to 16, 2027. The conference is soliciting state-of-the-art research papers in the following areas of interest, but not limited:

  • Foundational Theories and Frontier Technologies of Generative AI and Foundation Models


    Foundation Models and Scaling Laws
    Large Language Models (LLMs) and Large Multimodal Models (LMMs)
    Representation Learning and Self-supervised Learning
    Diffusion Models and Generative Architectures
    Parameter-efficient Fine-tuning (PEFT) and Model Adaptation
    Foundation Model Theory and Emerging Capabilities
    Transformer Architecture Improvements and Novel Neural Network Structures
    Instruction Following and Capability Elicitation of Foundation Models

  • Multimodal Foundation Models and Cross-modal Intelligent Generation


    Vision-Language Models
    Multimodal Representation Learning
    Cross-modal Retrieval and Alignment
    Text-to-Image, Video and Audio Generation
    Multimodal Reasoning and Understanding
    Human-centric Multimodal Interaction
    Multimodal Large Model Pre-training and Alignment
    3D Generation and Spatial Multimodal Modeling




  • Embodied Intelligence and Autonomous Agents: Perception, Decision-making and Interaction


    Embodied AI and Intelligent Robotics
    Autonomous Agents and Multi-agent Systems
    Agent Planning, Memory and Tool Learning
    Human-Robot Collaboration
    Digital Humans and Virtual Agents
    Intelligent Perception and Interactive Learning
    Reinforcement Learning and Embodied Control Policies
    World Models and Simulation Environment Construction





  • Trustworthy Generative AI: Safety, Governance and Ethics


    AI Safety and Alignment
    Trustworthy and Explainable AI
    Privacy-preserving AI and Federated Learning
    AI Governance, Regulations and Compliance
    Adversarial Robustness and Content Security
    Deepfake Detection and Content Provenance
    AI Risk Assessment and Safety Testing
    Watermarking and Copyright Protection for Generative Content

  • AI-driven Scientific Discovery and Domain-specific Intelligence


    AI for Scientific Discovery
    AI in Healthcare and Life Sciences
    AI for Manufacturing and Industrial Intelligence
    AI in Finance, Business and Digital Economy
    Smart Cities, Transportation and Energy
    AI Applications in Education and Public Services
    AI for Materials Discovery and Chemistry
    AI for Climate Science and Environmental Sustainability

  • Efficient Training, Inference Optimization and Evaluation Benchmarks for Large Language Models


    Large-scale Pre-training Techniques
    Efficient Inference and Model Compression
    Prompt Engineering and In-context Learning
    Retrieval-Augmented Generation (RAG)
    RLHF and Preference Optimization
    Benchmarking and Evaluation of Foundation Models
    Long-context Modeling and Efficient Attention Mechanisms
    Model Distillation and Knowledge Transfer

  • Generative Content Creation and Digital Media Intelligence


    AI-generated Content (AIGC)
    AI-assisted Creative Design
    Generative Media, Animation and Virtual Production
    Intelligent Music, Speech and Video Generation
    Digital Art, Cultural Heritage and Creative Industries
    Personalized Content Generation and Recommendation
    Controllable Generation and Style Transfer
    Real-time Rendering and Neural Graphics

  • Data-centric Artificial Intelligence: Synthetic Data and High-quality Data Construction


    Synthetic Data Generation
    Data Quality Assessment and Enhancement
    Data Annotation and Automated Labeling
    Data Governance and Lifecycle Management
    Privacy-aware Data Sharing and Data Security
    Knowledge Graphs and Data-centric AI
    Data Flywheel and Active Learning
    Multi-source Data Fusion and Data Orchestration

  • Human-AI Hybrid Intelligence and Adaptive Interactive Decision Systems


    Human-AI Collaboration
    Intelligent Decision Support Systems
    Conversational AI and Dialogue Systems
    Personalized Intelligent Assistants
    Adaptive Human-Computer Interaction
    Explainable Decision-making and Causal Reasoning
    Affective Computing and Natural User Interfaces
    Multi-turn Dialogue State Tracking and Context Management


  • Systems Engineering and Industrial Platform Technologies for Generative AI


    AI Infrastructure and Computing Platforms MLOps and LLMOps
    Cloud-edge-device Collaborative AI
    Model Serving, Deployment and Optimization
    Open-source Foundation Models and AI Ecosystems
    Heterogeneous Computing and AI Chip Optimization
    AI Agent Platforms and Low-code Development
    Distributed Training and Inference System Architecture for Large Models

© Copyrights AIGT 2027. | Nanjing, China.