TartuNLP at SemEval-2025 Task 5: Subject Tagging as Two-Stage Information Retrieval

AbstractWe present our submission to the Task 5 of SemEval-2025. We frame the task as an information retrieval problem, where the document content is used to retrieve subject tags from a large subject taxonomy. We leverage two types of encoder models to build a two-stage information retrieval system—a bi-encoder for coarse-grained candidate extraction at the first stage, and a cross-encoder for fine-grained re-ranking at the second stage.