📚︎ Track 1: Artificial Intelligence Fundamentals

Machine learning and deep learning theories and algorithms

Reinforcement learning and decision optimization

Multimodal data fusion and representation learning

Computer vision and intelligent perception

Natural language processing and speech technology

Explainable AI (XAI) and trustworthy AI

Knowledge graphs and data mining

Distributed, edge, and cloud intelligent computing

📚︎ Track 2: Large Models (LLM)

Large language model (LLM) architecture and training

Instruction fine-tuning and prompt engineering

Retrieval-augmented generation (RAG)

Multimodal large models

Reasoning, planning, and agent collaboration in large models

Evaluation, safety, and alignment of large models

Domain-specific large models and industrial fine-tuning

Inference acceleration and edge deployment of large models

📚︎ Track 3: Intelligent Agents

Multi-agent systems and coordinated decision-making

Autonomous agents and task planning

LLM-driven agents

Embodied intelligence and intelligent robotics

Applications of intelligent agents in industry

Human–agent collaboration and human–computer interaction

Digital twins and virtual agents

Cognition, memory, and continual learning of intelligent agents