Call for Papers
Submit on EasyChairSeptember 16, 2026 AoE
Important Dates
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Submissions OpenJuly 15, 2026
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Submission Deadline
September 13, 2026
September 16, 2026 AoEUpcoming -
Accept/Reject NotificationSeptember 23, 2026 AoEUpcoming
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WorkshopNovember 8, 2026Upcoming
We invite researchers to submit their latest work to the KEIR @ CIKM 2026 workshop on various aspects of knowledge-enhanced information retrieval, including models, techniques, data collection, and evaluation methodologies. We welcome both short and long papers reporting original or work-in-progress research, as well as position, applied, and resource papers and demos.
We broadly define external knowledge as any resource beyond a model's parametric memory—unstructured or structured, gold or synthetic, and increasingly multimodal—including text corpora, tabular data, semi-structured user preferences, knowledge graphs, and databases. We particularly encourage contributions targeting knowledge-intensive, domain-sensitive fields where factuality, trust, and discovery are paramount—especially medical applications such as biomedical question answering and clinical decision support with evidence grounding over domain ontologies and patient records, alongside law, finance, and science at large.
Relevant Topics Include, but are not limited to:
- Knowledge-enhanced information retrieval and recommendation models, both representational and generative (e.g., generating document identifiers grounded in domain knowledge)
- Knowledge-enhanced approaches for data augmentation and query processing, including query parsing, expansion, and reformulation
- Knowledge-enhanced agentic IR: LLM agents that plan, reason, and decide when, what, and how to retrieve, navigate structured knowledge, and curate and link knowledge
- Self-evolving, dynamic-knowledge, and automated discovery frameworks
- Multimodal knowledge sources and modality-specific IR techniques (e.g., visual patches from PDF pages, subgraph retrieval from knowledge graphs)
- Test-time training and adaptation of retrievers and language models to incorporate new knowledge
- Efficiency at both training and inference time (e.g., knowledge distillation, adapters, and latency reduction)
- Evaluation methodologies for knowledge-enhanced IR, including uncertainty quantification, interpretability, attribution, and analysis of bias and fairness
- Applications of knowledge-enhanced retrieval, such as dialogue systems, question answering, and summarization in domain-specific settings (e.g., biomedical literature search and clinical decision support)