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LLM-Enhanced Dual-Branch Learning for Large-Scale Multi-Label Text Classification

arXiv · AI, language, vision and robotics · article · Sep 11, 2026 · UTC

Large-scale multi-label text classification assigns a small subset of relevant labels to each document from a vocabulary containing thousands or tens of thousands of candidate labels. Although pretrained language models have improved semantic text representations, most representation-based approaches center their prediction pipelines on a primary encoder or combine auxiliary features within a single ranker. The complementarity between heterogeneous language models therefore remains insufficiently explored. We propose DualMLC, a dual-branch framework that processes the same document through an

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