Sequential Recommendation on Office (test)
0.24NDCG@1RecNet
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| RecNetBackbone=Deepseek-R1-Distill-Qwen-32B, embedding dimension=1282026.01 | 0.24 | 0.4373 | 0.5933 | |
| KGLAAugmentation=knowledge graphs2026.01 | 0.21 | 0.3845 | 0.5435 | |
| BPR-fullmode=full datasets2026.01 | 0.2 | 0.3341 | 0.4812 | |
| SASRec-fullmode=full datasets2026.01 | 0.19 | 0.3761 | 0.5228 | |
| AgentCF2026.01 | 0.19 | 0.3506 | 0.5261 | |
| AgentCF++Architecture=dual-layer memory2026.01 | 0.1867 | 0.3688 | 0.5208 | |
| LLMRankmode=zero-shot ranker, Backbone=ChatGPT2026.01 | 0.16 | 0.3272 | 0.4832 | |
| SASRec-samplemode=sampled datasets2026.01 | 0.09 | 0.2675 | 0.3894 | |
| Pop2026.01 | 0.06 | 0.148 | 0.2137 | |
| BPR-samplemode=sampled datasets2026.01 | 0.05 | 0.2461 | 0.2938 |