About us

The rapid evolution of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) techniques has opened numerous opportunities for developing intelligent systems capable of autonomous decision-making and adaptive information processing. This workshop focuses on the intersection of advanced AI techniques and domain-specific applications within the broader context of ambient intelligence and artificial intelligence, addressing the gap between general-purpose LLMs and specialised requirements in legal, medical, technical, and regulatory contexts.

Important Dates

Fri, May 8, 2026

Abstract registration deadline

Fri, May 8, 2026

Submission deadline

Call For Paper

RAG and Advanced Information Retrieval

GraphRAG and knowledge graph integration

Retrieval optimisation for specialised corpora

Domain-Specific Language Models

Fine-tuning and specialisation of foundation models

Few-shot and zero-shot learning in specialised contexts

Evaluation benchmarks for domain-specific LLMs

Agentic AI Architectures

Memory systems for long-context reasoning

Tool use and external API integration

Multi-agent coordination and communication

Frameworks for agentic systems and benchmarking

Document processing and analysis automation

Workflow automation using LLM agents

Natural language interfaces for complex systems

Process optimisation through intelligent agents

Applications in Specialised Domains

Human in the loop AI

Trust and transparency in automated systems

Collaborative intelligence between humans and AI agents

User preference modelling and personalisation

Metrics for RAG system performance

Domain-specific evaluation frameworks

Robustness testing and adversarial scenarios

We invite a broad spectrum of contributions, ranging from original research and architectural proposals to industrial use cases and technological demonstrators. We specifically welcome work addressing the rigorous application of AI and emerging technologies in industrial environments, including research summaries and ongoing PhD studies.

Committee

Organizing Committee

Fábio Silva

CIICESI, Escola Superior de Tecnologia e Gestão, Instituto Politécnico do Porto, Portugal

Ricardo Santos