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SRCB at SemEval-2026 Task 5: A Multi-Target Finetuning Framework for Large Language Models with Joint Regression and Text Generation

This paper presents the winning system for SemEval-2026 Task 5 on rating the plausibility of word senses in ambiguous stories, demonstrating the effectiveness of unified regressive–generative modeling for fine-grained plausibility estimation.

Yuming Zhang, Jun-Yu Zhou, Hong-Yu Li et al. · 0 citations

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