Asia Conference on Machine Learning and Computing ACMLC on July 10-12, 2026 in Beijing, China

CALL FOR PAPERS:

Authors are invited to submit full papers describing original research work in areas including, but not limited to:

TRACK 1: Large Language Model Agents Theory and Applications

Multimodal LLM Agents: Vision-language-audio integrated agent systems

Agent Planning and Reasoning: Task decomposition, path planning, and logical reasoning with large models

Tool Use and API Integration: External tool invocation and system integration capabilities for agents

Multi-Agent Collaboration: Large model-driven multi-agent coordination and cooperation mechanisms

Agent Safety and Alignment: Safety assurance and value alignment for trustworthy AI agents

Domain-Specific Agents: Specialized agents for vertical domains such as healthcare, finance, and education

Agent Evaluation and Benchmarking: Capability assessment frameworks and standardized testing for intelligent agents

Agent Memory and Learning: Long-term memory systems and continual learning for persistent agents

Human-Agent Interaction: Natural language interfaces and interaction design for AI agents

Agent Architecture and Infrastructure: Scalable frameworks and platforms for deploying LLM agents

TRACK 2: Social Computing and Human-AI Collaboration

Computational Social Science: Simulation, prediction, and modeling of social phenomena and communities

Human-AI Collaboration Patterns: Workflow design for AI agent and human cooperation

Social Network Dynamics: Behavioral pattern mining and analysis in large-scale social networks

Collective Intelligence: Group decision-making, crowdsourcing, and distributed problem-solving systems

Agent-Driven Social Modeling: Using AI agents for social behavior analysis and human preference learning

Social Media and Cultural Computing: Content analysis, sentiment analysis, cross-cultural AI systems, and bias mitigation

AI Ethics and Social Impact: Research on AI systems' effects on social structures, relationships, and equity

Explainable and Socially-Aware AI: Interpretable AI systems that understand and adapt to social contexts

Digital Governance and Policy: AI applications in public administration, policy-making, and social governance

Social Robotics and Interaction: Human-robot interaction in social and collaborative contexts

Digital Humanities: AI applications in humanities research and cultural heritage preservation

For details about topics, please visit at http://www.acmlc.org/topics.html

Name: etpub