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Add new model DCNv3 (#109)
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salmon1802 authored Aug 7, 2024
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Expand Up @@ -72,23 +72,24 @@ Click-through rate (CTR) prediction is a critical task for various industrial ap
| 36 | AAAI'23 | [FinalMLP](./model_zoo/FinalMLP) | [FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction](https://arxiv.org/abs/2304.00902) :triangular_flag_on_post:**Huawei** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/FinalMLP) | `torch` |
| 37 | SIGIR'23 | [FinalNet](./model_zoo/FinalNet) | [FINAL: Factorized Interaction Layer for CTR Prediction](https://dl.acm.org/doi/10.1145/3539618.3591988) :triangular_flag_on_post:**Huawei** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/FinalNet) | `torch` |
| 38 | CIKM'23 | [GDCN](./model_zoo/GDCN) | [Towards Deeper, Lighter and Interpretable Cross Network for CTR Prediction](https://dl.acm.org/doi/pdf/10.1145/3583780.3615089) :triangular_flag_on_post:**Microsoft** | | `torch` |
| 39 | Arxiv'24 | [DCNv3](./model_zoo/DCNv3) | [DCNv3: Towards Next Generation Deep Cross Network for Click-Through Rate Prediction](https://arxiv.org/abs/2407.13349) :triangular_flag_on_post:**AHU, Huawei** | [:arrow_upper_right:](https://github.com/salmon1802/DCNv3/tree/master/checkpoints) | `torch` |
|<tr><th colspan=6 align="center">:open_file_folder: **Behavior Sequence Modeling**</th></tr>|
| 39 | KDD'18 | [DIN](./model_zoo/DIN) | [Deep Interest Network for Click-Through Rate Prediction](https://www.kdd.org/kdd2018/accepted-papers/view/deep-interest-network-for-click-through-rate-prediction) :triangular_flag_on_post:**Alibaba** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/DIN) | `torch` |
| 40 | AAAI'19 | [DIEN](./model_zoo/DIEN) | [Deep Interest Evolution Network for Click-Through Rate Prediction](https://arxiv.org/abs/1809.03672) :triangular_flag_on_post:**Alibaba** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/DIEN) | `torch` |
| 41 | DLP-KDD'19 | [BST](./model_zoo/BST) | [Behavior Sequence Transformer for E-commerce Recommendation in Alibaba](https://arxiv.org/abs/1905.06874) :triangular_flag_on_post:**Alibaba** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/BST) | `torch` |
| 42 | CIKM'20 | [DMIN](./model_zoo/DMIN) | [Deep Multi-Interest Network for Click-through Rate Prediction](https://dl.acm.org/doi/10.1145/3340531.3412092) :triangular_flag_on_post:**Alibaba** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/DMIN) | `torch` |
| 43 | AAAI'20 | [DMR](./model_zoo/DMR) | [Deep Match to Rank Model for Personalized Click-Through Rate Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/5346) :triangular_flag_on_post:**Alibaba** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/DMR) | `torch` |
| 44 | Arxiv'21 | [ETA](./model_zoo/ETA) | [End-to-End User Behavior Retrieval in Click-Through RatePrediction Model](https://arxiv.org/abs/2108.04468) :triangular_flag_on_post:**Alibaba** | | `torch` |
| 45 | CIKM'22 | [SDIM](./model_zoo/SDIM) | [Sampling Is All You Need on Modeling Long-Term User Behaviors for CTR Prediction](https://arxiv.org/abs/2205.10249) :triangular_flag_on_post:**Meituan** | | `torch` |
| 40 | KDD'18 | [DIN](./model_zoo/DIN) | [Deep Interest Network for Click-Through Rate Prediction](https://www.kdd.org/kdd2018/accepted-papers/view/deep-interest-network-for-click-through-rate-prediction) :triangular_flag_on_post:**Alibaba** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/DIN) | `torch` |
| 41 | AAAI'19 | [DIEN](./model_zoo/DIEN) | [Deep Interest Evolution Network for Click-Through Rate Prediction](https://arxiv.org/abs/1809.03672) :triangular_flag_on_post:**Alibaba** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/DIEN) | `torch` |
| 42 | DLP-KDD'19 | [BST](./model_zoo/BST) | [Behavior Sequence Transformer for E-commerce Recommendation in Alibaba](https://arxiv.org/abs/1905.06874) :triangular_flag_on_post:**Alibaba** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/BST) | `torch` |
| 43 | CIKM'20 | [DMIN](./model_zoo/DMIN) | [Deep Multi-Interest Network for Click-through Rate Prediction](https://dl.acm.org/doi/10.1145/3340531.3412092) :triangular_flag_on_post:**Alibaba** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/DMIN) | `torch` |
| 44 | AAAI'20 | [DMR](./model_zoo/DMR) | [Deep Match to Rank Model for Personalized Click-Through Rate Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/5346) :triangular_flag_on_post:**Alibaba** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/DMR) | `torch` |
| 45 | Arxiv'21 | [ETA](./model_zoo/ETA) | [End-to-End User Behavior Retrieval in Click-Through RatePrediction Model](https://arxiv.org/abs/2108.04468) :triangular_flag_on_post:**Alibaba** | | `torch` |
| 46 | CIKM'22 | [SDIM](./model_zoo/SDIM) | [Sampling Is All You Need on Modeling Long-Term User Behaviors for CTR Prediction](https://arxiv.org/abs/2205.10249) :triangular_flag_on_post:**Meituan** | | `torch` |
|<tr><th colspan=6 align="center">:open_file_folder: **Dynamic Weight Network**</th></tr>|
| 46 | NeurIPS'22 | [APG](./model_zoo/APG) | [APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction](https://arxiv.org/abs/2203.16218) :triangular_flag_on_post:**Alibaba** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/APG) | `torch` |
| 47 | KDD'23 | [PPNet](./model_zoo/PEPNet) | [PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information](https://arxiv.org/abs/2302.01115) :triangular_flag_on_post:**KuaiShou** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/PPNet) | `torch` |
| 47 | NeurIPS'22 | [APG](./model_zoo/APG) | [APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction](https://arxiv.org/abs/2203.16218) :triangular_flag_on_post:**Alibaba** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/APG) | `torch` |
| 48 | KDD'23 | [PPNet](./model_zoo/PEPNet) | [PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information](https://arxiv.org/abs/2302.01115) :triangular_flag_on_post:**KuaiShou** | [:arrow_upper_right:](https://github.com/reczoo/BARS/tree/main/ranking/ctr/PPNet) | `torch` |
|<tr><th colspan=6 align="center">:open_file_folder: **Multi-Task Modeling**</th></tr>|
| 48 | MachineLearn'97 | [SharedBottom](./model_zoo/multitask/SharedBottom) | [Multitask Learning](https://link.springer.com/article/10.1023/A:1007379606734) | | `torch` |
| 49 | KDD'18 | [MMoE](./model_zoo/multitask/MMOE) | [Modeling Task Relationships in Multi-task Learning with Multi-Gate Mixture-of-Experts](https://dl.acm.org/doi/pdf/10.1145/3219819.3220007) :triangular_flag_on_post:**Google** | | `torch` |
| 50 | KDD'18 | [PLE](./model_zoo/multitask/PLE) | [Progressive Layered Extraction (PLE): A Novel Multi-Task Learning (MTL) Model for Personalized Recommendations](https://dl.acm.org/doi/10.1145/3383313.3412236) :triangular_flag_on_post:**Tencent** | | `torch` |
| 49 | MachineLearn'97 | [SharedBottom](./model_zoo/multitask/SharedBottom) | [Multitask Learning](https://link.springer.com/article/10.1023/A:1007379606734) | | `torch` |
| 50 | KDD'18 | [MMoE](./model_zoo/multitask/MMOE) | [Modeling Task Relationships in Multi-task Learning with Multi-Gate Mixture-of-Experts](https://dl.acm.org/doi/pdf/10.1145/3219819.3220007) :triangular_flag_on_post:**Google** | | `torch` |
| 51 | KDD'18 | [PLE](./model_zoo/multitask/PLE) | [Progressive Layered Extraction (PLE): A Novel Multi-Task Learning (MTL) Model for Personalized Recommendations](https://dl.acm.org/doi/10.1145/3383313.3412236) :triangular_flag_on_post:**Tencent** | | `torch` |
|<tr><th colspan=6 align="center">:open_file_folder: **Multi-Domain Modeling**</th></tr>|
| 51 | KDD'23 | PEPNet | [PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information](https://arxiv.org/abs/2302.01115) :triangular_flag_on_post:**KuaiShou** | | `torch` |
| 52 | KDD'23 | PEPNet | [PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information](https://arxiv.org/abs/2302.01115) :triangular_flag_on_post:**KuaiShou** | | `torch` |

## Benchmarking

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