Sequential Recommendation on Yelp (test)
4.95H@10MPT
Evaluation results
| Method | Links | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| MPTTraining Protocol=Pre-training & Fine-tuning, ID-based=false, Adaptor=+LoRA2026.01 | 4.95 | — | — | — | 0.64 | 8.32 | 2.41 | 3.25 | |
| SASRec+Training Protocol=Training from scratch, ID-based=true2026.01 | 4.66 | — | — | — | 0.31 | 7.96 | 2.09 | 2.92 | |
| MPTTraining Protocol=Pre-training & Fine-tuning, ID-based=false, Adaptor=Lightweight Input Adaptor2026.01 | 4.61 | — | — | — | 0.61 | 7.83 | 2.24 | 3.05 | |
| HSTUTraining Protocol=Training from scratch, ID-based=true2026.01 | 4.53 | — | — | — | 0.51 | 7.73 | 2.15 | 2.95 | |
| TIGER + OursCategory=Token-weighted GR2026.01 | 4.19 | 2.64 | 1.75 | 2.25 | — | — | — | — | |
| Qwen2.5Training Protocol=Pre-training & Fine-tuning, ID-based=false2026.01 | 4.11 | — | — | — | 0.6 | 6.82 | 2.04 | 2.72 | |
| TIGER + IGDCategory=Token-weighted GR2026.01 | 4.01 | 2.45 | 1.58 | 2.08 | — | — | — | — | |
| TIGER + RankCategory=Token-weighted GR2026.01 | 3.96 | 2.41 | 1.55 | 2.05 | — | — | — | — | |
| TIGERCategory=Token-weighted GR2026.01 | 3.91 | 2.4 | 1.55 | 2.02 | — | — | — | — | |
| TIGER + CFTCategory=Token-weighted GR2026.01 | 3.9 | 2.39 | 1.54 | 2.02 | — | — | — | — | |
| TIGER + PosCategory=Token-weighted GR2026.01 | 3.87 | 2.39 | 1.54 | 2.01 | — | — | — | — | |
| UniSRecTraining Protocol=Pre-training & Fine-tuning, ID-based=false2026.01 | 3.43 | — | — | — | 0.5 | 5.67 | 1.7 | 2.26 | |
| FMLPRecTraining Protocol=Training from scratch, ID-based=true2026.01 | 3.34 | — | — | — | 0.05 | 6.06 | 1.38 | 2.07 | |
| AdaTTABase Model=SASRec, Augmentation Strategy=Adaptive2026.04 | 2.99 | 1.74 | 1.07 | 1.47 | — | 5.03 | — | — | |
| SASRecTraining Protocol=Training from scratch, ID-based=true2026.01 | 2.98 | — | — | — | 0.01 | 5.39 | 1.23 | 1.84 | |
| SASRec + TMask-RBase Model=SASRec, Augmentation Strategy=TMask-R2026.04 | 2.97 | 1.71 | 1.06 | 1.46 | — | 4.99 | — | — | |
| E4SRecTraining Protocol=Pre-training & Fine-tuning, ID-based=true2026.01 | 2.91 | — | — | — | 0.35 | 5.13 | 1.39 | 1.95 | |
| SASRec + ReorderBase Model=SASRec, Augmentation Strategy=Reorder2026.04 | 2.86 | 1.64 | 1.01 | 1.4 | — | 4.82 | — | — | |
| SASRec + CropBase Model=SASRec, Augmentation Strategy=Crop2026.04 | 2.84 | 1.62 | 1 | 1.4 | — | 4.85 | — | — | |
| SASRecCategory=Traditional2026.01 | 2.79 | 1.66 | 0.99 | 1.37 | — | — | — | — | |
| SASRec + TNoiseBase Model=SASRec, Augmentation Strategy=TNoise2026.04 | 2.78 | 1.62 | 1.02 | 1.4 | — | 4.62 | — | — | |
| SASRec + TMask-BBase Model=SASRec, Augmentation Strategy=TMask-B2026.04 | 2.68 | 1.54 | 0.96 | 1.32 | — | 4.6 | — | — | |
| SASRec + SubstituteBase Model=SASRec, Augmentation Strategy=Substitute2026.04 | 2.58 | 1.45 | 0.9 | 1.26 | — | 4.46 | — | — | |
| SASRec + InsertBase Model=SASRec, Augmentation Strategy=Insert2026.04 | 2.57 | 1.45 | 0.9 | 1.26 | — | 4.37 | — | — | |
| SASRec (Base)Base Model=SASRec, Augmentation Strategy=None2026.04 | 2.53 | 1.42 | 0.88 | 1.24 | — | 4.3 | — | — | |
| RecFormerTraining Protocol=Pre-training & Fine-tuning, ID-based=false2026.01 | 2.47 | — | — | — | 0.34 | 4.29 | 1.21 | 1.66 | |
| GRU4RecTraining Protocol=Training from scratch, ID-based=true2026.01 | 2.46 | — | — | — | 0.28 | 4.48 | 1.16 | 1.66 | |
| GRU4RecCategory=Traditional2026.01 | 2.32 | 1.43 | 0.93 | 1.21 | — | — | — | — | |
| AdaTTABase Model=GRU4Rec, Augmentation Strategy=Adaptive2026.04 | 2.17 | 1.19 | 0.71 | 1.03 | — | 3.81 | — | — | |
| GRU4Rec + TMask-RBase Model=GRU4Rec, Augmentation Strategy=TMask-R2026.04 | 2.07 | 1.14 | 0.69 | 0.99 | — | 3.64 | — | — | |
| GRU4Rec + InsertBase Model=GRU4Rec, Augmentation Strategy=Insert2026.04 | 2.06 | 1.11 | 0.66 | 0.96 | — | 3.66 | — | — | |
| GRU4Rec + SubstituteBase Model=GRU4Rec, Augmentation Strategy=Substitute2026.04 | 2.03 | 1.11 | 0.66 | 0.96 | — | 3.64 | — | — | |
| GRU4Rec + CropBase Model=GRU4Rec, Augmentation Strategy=Crop2026.04 | 2.02 | 1.11 | 0.67 | 0.96 | — | 3.51 | — | — | |
| GRU4Rec + TMask-BBase Model=GRU4Rec, Augmentation Strategy=TMask-B2026.04 | 2.02 | 1.12 | 0.69 | 0.97 | — | 3.62 | — | — | |
| GRU4Rec + ReorderBase Model=GRU4Rec, Augmentation Strategy=Reorder2026.04 | 1.9 | 1.01 | 0.61 | 0.89 | — | 3.49 | — | — | |
| GRU4Rec (Base)Base Model=GRU4Rec, Augmentation Strategy=None2026.04 | 1.58 | 0.82 | 0.48 | 0.72 | — | 2.98 | — | — | |
| GRU4Rec + TNoiseBase Model=GRU4Rec, Augmentation Strategy=TNoise2026.04 | 1.44 | 0.72 | 0.43 | 0.66 | — | 2.75 | — | — |