mlsanityData to 14 Oct 2026

PREMISE: Matching-based Prediction for Accurate Review Recommendation

arXiv 2505.01255 ↗First posted 2 May 2025cs.CL cs.IR cs.MMcited by 0

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Abstract (arXiv)

We present PREMISE (PREdict with Matching ScorEs), a new architecture for the matching-based learning in the multimodal fields for the multimodal review helpfulness (MRHP) task. Distinct to previous fusion-based methods which obtains multimodal representations via cross-modal attention for downstream tasks, PREMISE computes the multi-scale and multi-field representations, filters duplicated semantics, and then obtained a set of matching scores as feature vectors for the downstream recommendation task. This new architecture significantly boosts the performance for such multimodal tasks whose context matching content are highly correlated to the targets of that task, compared to the state-of-the-art fusion-based methods. Experimental results on two publicly available datasets show that PREMISE achieves promising performance with less computational cost.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 39 of its 58 references that are in the map. First posted on arXiv 2 May 2025.

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39 of 58 references.

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