| Improving multi-target tracking via social grouping Z Qin, CR Shelton CVPR 2012, 2012 | 179 | 2012 |
| Transformer Memory as a Differentiable Search Index Y Tay, VQ Tran, M Dehghani, J Ni, D Bahri, H Mehta, Z Qin, K Hui, Z Zhao, ... NeurIPS 2022, 2022 | 175 | 2022 |
| Charformer: Fast Character Transformers via Gradient-based Subword Tokenization Y Tay, VQ Tran, S Ruder, J Gupta, HW Chung, D Bahri, Z Qin, ... ICLR 2022, 2022 | 122 | 2022 |
| Are Neural Rankers Still Outperformed By Gradient Boosted Decision Tree? Z Qin, L Yan, H Zhuang, Y Tay, RK Pasumarthi, X Wang, M Bendersky, ... ICLR 2021, 2021 | 111 | 2021 |
| Large language models are effective text rankers with pairwise ranking prompting Z Qin, R Jagerman, K Hui, H Zhuang, J Wu, J Shen, T Liu, J Liu, D Metzler, ... NAACL 2024, 2024 | 106 | 2024 |
| Are Pre-trained Convolutions Better than Pre-trained Transformers? Y Tay, M Dehghani, J Gupta, D Bahri, V Aribandi, Z Qin, D Metzler ACL 2021, 2021 | 79 | 2021 |
| RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses H Zhuang, Z Qin, R Jagerman, K Hui, J Ma, J Lu, J Ni, X Wang, ... SIGIR 2023, 2023 | 68 | 2023 |
| Multitask Mixture of Sequential Experts for User Activity Streams Z Qin, Y Cheng, Z Zhao, SZ Chen, D Metzler, J Qin KDD 2020, 2020 | 60 | 2020 |
| An online learned elementary grouping model for multi-target tracking X Chen, Z Qin, L An, B Bhanu CVPR 2014, 2014 | 58 | 2014 |
| Attribute-based Propensity for Unbiased Learning in Recommender Systems: Algorithm and Case Studies Z Qin, SJ Chen, D Metzler, Y Noh, J Qin, X Wang KDD 2020, 2020 | 47 | 2020 |
| Query Expansion by Prompting Large Language Models R Jagerman, H Zhuang, Z Qin, X Wang, M Bendersky The First Workshop on Generative Information Retrieval (Gen-IR), 2023 | 44 | 2023 |
| Hawkes Process Inference with Missing Data CR Shelton, Z Qin, C Shetty AAAI Conference on Artificial Intelligence (AAAI), 2018 | 42 | 2018 |
| Social Grouping for Multi-target Tracking and Head Pose Estimation in Video Z Qin, C Shelton IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2015 | 35 | 2015 |
| OmniNet: Omnidirectional Representations from Transformers Y Tay, M Dehghani, V Aribandi, J Gupta, P Pham, Z Qin, D Bahri, DC Juan, ... ICML 2021, 2021 | 34 | 2021 |
| Diversification-Aware Learning to Rank using Distributed Representation L Yan, Z Qin, RK Pasumarthi, X Wang, M Bendersky Proceedings of the Web Conference (WWW), 2021 | 34 | 2021 |
| Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search P Li, Z Qin, X Wang, D Metzler KDD 2019, 2019 | 34 | 2019 |
| Cross-Positional Attention for Debiasing Clicks H Zhuang, Z Qin, X Wang, M Bendersky, X Qian, P Hu, C Chen Proceedings of the Web Conference (WWW), 2021 | 33 | 2021 |
| Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels H Zhuang, Z Qin, K Hui, J Wu, L Yan, X Wang, M Berdersky NAACL 2024, 2024 | 32 | 2024 |
| Non-Clicks Mean Irrelevant? Propensity Ratio Scoring As a Correction N Wang, Z Qin, X Wang, H Wang WSDM 2021, 2021 | 25 | 2021 |
| Improving Recommendation Quality at Google Drive SJ Chen, Z Qin, ZT Wilson, BL Calaci, MR Rose, RL Evans, SR Abraham, ... KDD 2020, 2020 | 21 | 2020 |
Michael BenderskyGoogle DeepMind在 google.com 的电子邮件经过验证
