Efficient Neural Document Ranking with Compact Representations

Project Overview

This project studies efficiency optimization in neural ranking for document search.

People

Publications

  • Y. Qiao, Y. Yang, S. He and T. Yang, Representation Sparsification with Hybrid Thresholding for Fast SPLADE-based Document Retrieval. Proc. of ACM conference on Research and Development in Information Retrieval, SIGIR'2023 .

  • Y. Qiao, Y. Yang, H. Lin, T. Yang, Optimizing Guided Traversal for Fast Learned Sparse Retrieval, Proc. of the ACM Web Conference 2023 (WWW ’23), May 1–5, 2023, Austin, TX, USA . PDF. Slides

  • Y. Yang, S. He, Y. Qiao, W. Xie, and T. Yang, Balanced Knowledge Distillation with Contrastive Learning for Document Re-ranking. Proc. of 9th ACM SIGIR/13th Inter. Conference on the Theory of Information Retrieval (ICTIR 2023).

  • Y. Qiao, S. Ji, C. Wang, J. Shao, T. Yang. Privacy-aware Document Retrieval with Two-level Inverted Indexing. To appear in Information Retrieval Journal.

Acknowledgment: This project is supported in part by NSF 2225942 (2022-2025). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.