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Found 3 papers, 2 papers with code
CIRP: Cross-Item Relational Pre-training for Multimodal Product Bundling
However, the cross-item relations have been under-explored in the current multimodal pre-train models.
MultiCBR: Multi-view Contrastive Learning for Bundle Recommendation
It does, however, have two limitations: 1) the two-view formulation does not fully exploit all the heterogeneous relations among users, bundles and items; and 2) the "early contrast and late fusion" framework is less effective in capturing user preference and difficult to generalize to multiple views.
CrossCBR: Cross-view Contrastive Learning for Bundle Recommendation
Recent methods usually take advantage of both user-bundle and user-item interactions information to obtain informative representations for users and bundles, corresponding to bundle view and item view, respectively.
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