The information retrieval (IR) community is moving from traditional human-driven search towards agentic search, where agents iteratively generate search queries, inspect retrieved documents, and repeat the process until sufficient evidence is gathered to produce a final answer. Agentic search is important because it can scale knowledge-intensive work and enable agents to interact with external knowledge. Despite its importance, existing tutorials cover agentic search only as part of broader topics.

We are excited to announce the tutorial "Agentic Search: Foundations, Optimization, and Long-Horizons", which will be held in person at the 35th ACM International Conference on Information and Knowledge Management (CIKM 2026) in Rome, Italy, on the afternoon of 7 November 2026. See the ACM Digital Library entry for the tutorial paper.

The tutorial is devoted entirely to agentic search. It covers three key topics: systematic optimization paradigms, with a focus on reinforcement learning (RL) methods; long-horizon agentic search, also known as deep research; and the evaluation of agentic search, especially for long-form report generation. It also features a live demonstration and hands-on session.

The tutorial is designed for students, researchers, and practitioners from both academia and industry. Participants will gain a comprehensive understanding of agentic search and learn to run a full agentic search pipeline themselves. Attendees are expected to have a basic understanding of machine learning, deep learning, and core IR concepts, such as indexing and relevance modeling, and the tutorial provides the background needed to follow every part.