| license: apache-2.0 | |
| task_categories: | |
| - text-ranking | |
| # TARQ Dataset | |
| This dataset is associated with the paper [Equip Pre-ranking with Target Attention by Residual Quantization](https://huggingface.co/papers/2509.16931). | |
| TARQ is a novel pre-ranking framework designed for industrial recommendation systems. It bridges the gap between efficiency and effectiveness by bringing the modeling power of Target Attention (TA) into the latency-critical pre-ranking stage through Residual Quantization. | |
| ## Resources | |
| - **Paper:** [Equip Pre-ranking with Target Attention by Residual Quantization](https://huggingface.co/papers/2509.16931) | |
| - **Code:** [https://github.com/zyody/tarq_sigir2026](https://github.com/zyody/tarq_sigir2026) |