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School of Computer Science and Technology
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LLMs can learn to intelligently route evidence across modalities to improve recommendations when data is missing, outperforming deterministic fusion methods by a significant margin.
Achieve up to 12% improvement in Rouge-LSum for multimodal tasks in edge-cloud settings by jointly training heterogeneous edge models with a server model, even with varying modality availability.
