| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Sequential Recommendation | Toys | Recall@56.01 | 42 | |
| Node Classification | Toys | Accuracy83.33 | 40 | |
| Sequential Recommendation | Toys (test) | NDCG@105.55 | 36 | |
| Denoising | Toys 256 x 256 x 31 MSI (test) | PSNR37.34 | 35 | |
| Tensor Completion | Toys 256 x 256 x 31 | PSNR48.67 | 35 | |
| Sequential Recommendation | Toys (Overall) | Hit Rate @108.46 | 24 | |
| Generative Recommendation | Toys | Recall@100.0846 | 23 | |
| Recommendation | Toys | Hit Ratio@100.1101 | 21 | |
| Sequential Recommendation | Toys | Recall@108.02 | 20 | |
| 3D Asset Reconstruction | Toys4k | CD0.0083 | 18 | |
| Node Clustering | Toys | NMI54.66 | 17 | |
| Node Classification | Toys MAGB | Accuracy80.92 | 13 | |
| Sequential Recommendation | Toys | HR@2012.1264 | 12 | |
| Sequential Recommendation | Toys | HR@107.26 | 11 | |
| Image-to-3D | Toys4K | CLIP Similarity89.34 | 11 | |
| Modality Retrieval | Toys | R@50.6534 | 11 | |
| Generative Recommendation | Toys | Ad Rate94.3 | 11 | |
| Sequential Recommendation | Toys | HR@57.83 | 11 | |
| Sequential Recommendation | Toys | Recall@58.96 | 9 | |
| Multi-view 3D generation | Toys4K | CD (10^-4)4.16 | 9 | |
| Multimodal Recommendation | Toys | Recall@32.14 | 9 | |
| Direct Recommendation | Toys | Hit Rate@558.93 | 9 | |
| Refinement of VFM-derived artifacts | Toys4k (synthetically corrupted) | mIoU0.858 | 8 | |
| Recommendation | Toys TIGER Backbone (Period 4) | Hit Rate @52.69 | 7 | |
| Recommendation | Toys TIGER Backbone (Period 3) | H@53.09 | 7 |