Axiomatically Regularized Pre-training for Ad hoc Search

Author:

Chen Jia1,Liu Yiqun1,Fang Yan1,Mao Jiaxin2,Fang Hui3,Yang Shenghao1,Xie Xiaohui1,Zhang Min1,Ma Shaoping1

Affiliation:

1. Tsinghua University, Beijing, China

2. Renmin University of China, Beijing, China

3. University of Delaware, Newark, DE, USA

Funder

Natural Science Foundation of China

Publisher

ACM

Reference51 articles.

1. Probabilistic models of information retrieval based on measuring the divergence from randomness

2. Siddhant Arora and Andrew Yates . 2019. Investigating Retrieval Method Selection with Axiomatic Features. arXiv preprint arXiv:1904.05737 ( 2019 ). Siddhant Arora and Andrew Yates. 2019. Investigating Retrieval Method Selection with Axiomatic Features. arXiv preprint arXiv:1904.05737 (2019).

3. Diagnosing BERT with Retrieval Heuristics

4. Wei-Cheng Chang , Felix X Yu , Yin-Wen Chang , Yiming Yang , and Sanjiv Kumar . 2020. Pre-training tasks for embedding-based large-scale retrieval. arXiv preprint arXiv:2002.03932 ( 2020 ). Wei-Cheng Chang, Felix X Yu, Yin-Wen Chang, Yiming Yang, and Sanjiv Kumar. 2020. Pre-training tasks for embedding-based large-scale retrieval. arXiv preprint arXiv:2002.03932 (2020).

5. A Hybrid Framework for Session Context Modeling;Chen Jia;ACM Transactions on Information Systems (TOIS),2021

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