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As LMs increasingly support tasks such as knowledge extraction, completion, and generation, robust and standardised evaluation remains a key challenge. Current approaches are often fragmented, heavily reliant on human judgement, and lack reproducibility, making it difficult to compare methods or build on prior work. ELMKE addresses this gap by fostering a community-driven effort to develop consistent, transparent, and scalable evaluation practices. The workshop brings together researchers and practitioners to share innovative methods, discuss limitations of existing approaches, and explore new paradigms for evaluating LM outputs. Particular attention is given to issues such as transparency, the role of human evaluation, and the broader implications of evaluation choices. In its fourth edition, ELMKE will feature presentations of recent research alongside interactive discussions aimed at shaping future directions. 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