Conference Information

ACMLC 2026: Asia Conference on Machine Learning and Computing

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ACMLC
Submission Date:
2026-06-01 Extended
Notification Date:
2026-07-01
Conference Date:
2026-07-10
Location:
Beijing, China
Years:
8
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Call For Papers

ACMLC 2026 (Asia Conference on Machine Learning and Computing) is an academic conference held in Beijing, China on 2026-07-10. The paper submission deadline is 2026-06-01 (extended). Acceptance notifications are sent on 2026-07-01.

Authors are invited to submit full papers describing original research work in areas including, but not limited to: (Note: Since this is a computer-related conference, please submit papers that are computer-oriented.) 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
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