MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels

1 code implementation • 13 May 2024 • Qi Chen, Xiubo Geng, Corby Rosset, Carolyn Buractaon, Jingwen Lu, Tao Shen, Kun Zhou, Chenyan Xiong, Yeyun Gong, Paul Bennett, Nick Craswell, Xing Xie, Fan Yang, Bryan Tower, Nikhil Rao, Anlei Dong, Wenqi Jiang, Zheng Liu, Mingqin Li, Chuanjie Liu, Zengzhong Li, Rangan Majumder, Jennifer Neville, Andy Oakley, Knut Magne Risvik, Harsha Vardhan Simhadri, Manik Varma, Yujing Wang, Linjun Yang, Mao Yang, Ce Zhang

Recent breakthroughs in large models have highlighted the critical significance of data scale, labels and modals.

Information Retrieval Retrieval

SPANN: Highly-efficient Billion-scale Approximate Nearest Neighbor Search

1 code implementation • NeurIPS 2021 • Qi Chen, Bing Zhao, Haidong Wang, Mingqin Li, Chuanjie Liu, Zengzhong Li, Mao Yang, Jingdong Wang

It stores the centroid points of the posting lists in the memory and the large posting lists in the disk.

SPANN: Highly-efficient Billion-scale Approximate Nearest Neighborhood Search

1 code implementation • NeurIPS 2021 • Qi Chen, Bing Zhao, Haidong Wang, Mingqin Li, Chuanjie Liu, Zengzhong Li, Mao Yang, Jingdong Wang

It stores the centroid points of the posting lists in the memory and the large posting lists in the disk.

DynaTune: Dynamic Tensor Program Optimization in Deep Neural Network Compilation

no code implementations • ICLR 2021 • Minjia Zhang, Menghao Li, Chi Wang, Mingqin Li

Recently, the DL compiler, together with Learning to Compile has proven to be a powerful technique for optimizing deep learning models.

Decision Making Uncertainty Quantification

AdaTune: Adaptive Tensor Program Compilation Made Efficient

no code implementations • NeurIPS 2020 • Menghao Li, Minjia Zhang, Chi Wang, Mingqin Li

Deep learning models are computationally intense, and implementations often have to be highly optimized by experts or hardware vendors to be usable in practice.