KEIR @ CIKM 2026: The Third Workshop on Knowledge-Enhanced Information Retrieval

Abstract

Much of modern information retrieval (IR) now relies on pretrained language models whose parametric knowledge has driven strong gains in semantic understanding. Yet, this knowledge is frozen at training time, opaque, and limited in its coverage of long-tail, domain-specific, and fast-changing information, yielding imprecise, factually inaccurate, or poorly grounded results. Knowledge-enhanced IR addresses this by augmenting retrieval systems---and the language models that power them---with external knowledge: unstructured or structured, gold or synthetic, increasingly across modalities. Large language models are now reshaping how this knowledge is acquired and integrated---for example, autonomous agents that plan, reason, and decide what to search; automated knowledge curation and linking; and systems that interleave retrieval and generation, learning when to consult external evidence and when to answer from parametric knowledge. The Third Workshop on Knowledge-Enhanced Information Retrieval (KEIR @ CIKM 2026) gathers researchers and practitioners from IR, natural language processing, data mining, and knowledge management to advance the principled integration of external knowledge into IR. KEIR welcomes both methodological and applied contributions, with particular attention to knowledge-intensive, domain-sensitive fields such as science, medicine, law, and finance, where factuality, trust, and discovery are paramount.