Abstract

Pretrained language models (PLMs) like BERT and GPT-4 have become foundational to modern information retrieval (IR) systems. However, existing PLM-based IR models primarily rely on knowledge learned during training for predictions, limiting their ability to access and incorporate external, up-to-date, or domain-specific information. Consequently, current IR systems struggle with semantic nuances, contextual relevance, and domain-specific challenges.

This workshop (KEIR @ ECIR 2025) serves as a platform to discuss innovative approaches that integrate external knowledge, aiming to enhance the effectiveness of information retrieval in a rapidly evolving technological landscape. Our goal is to bring together researchers from academia and industry to explore various aspects of knowledge-enhanced information retrieval.

Call for Papers

We invite researchers to submit their latest work to the KEIR @ ECIR 2025 workshop on various aspects of knowledge-enhanced information retrieval, including models, techniques, data collection, and evaluation methodologies. Topics covered will include, but are not limited to:

• Knowledge-enhanced information retrieval models
• Knowledge-enhanced approaches for query processing, including query parsing, query expansion, relevance feedback, and query reformulation
• Knowledge-enhanced recommendation models
• Knowledge-enhanced language models for retrieval
• Data augmentation for knowledge-enhanced information retrieval
• Large language model enhanced information retrieval
• Data collection for knowledge-enhanced information retrieval
• Knowledge-enhanced retrieval-augmented generation models
• Knowledge-aware fine-tuning and optimization methods for large language models tailored to IR systems
• Applications of knowledge-enhanced retrievals, such as dialogue systems, question answering, summarisation, and other domain-specific applications
• Evaluation methodologies for knowledge-enhanced retrieval
• The interpretability and analysis of knowledge-enhanced models for IR, including potential biases, fairness, and ethical considerations

Submission Guidelines

We invite authors to submit papers written in English. Submissions may range in length from a minimum of 6 pages to a maximum of 12 pages; however, references and supplementary materials may exceed this page count without limitation. In order to facilitate a double-blind review process, authors must ensure that submissions are fully anonymized. Please note that we do not impose a specific anonymity period prior to submission.

The papers (.pdf format) should be submitted using the EasyChair submission system at https://easychair.org/conferences/?conf=keirecir2025. Authors should consult Springer’s authors’ guidelines and use their proceedings templates to prepare the submission. The Microsoft Word and LaTeX versions of the template can be found at https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines. Submissions to KEIR @ ECIR 2025 will be peer-reviewed on the basis of technical quality, relevance to workshop topics, originality, significance, clarity, etc.