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Project Overview

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

People

Parker Carlson
Shanxiu He
Yifan Qiao
Wentai Xie
Yingrui Yang
Tao Yang

Publications

P. Carlson, W. Xie, S. He, and T. Yang. Dynamic Superblock Pruning for Fast Learned Sparse Retrieval. To appear in Proc. of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025)
S. He, W. Xie, Y. Qiao, P. Carlson, and T. Yang. Low-Cost Document Retrieval with Dense Pseudo-Query Encoding. To appear in Proc. of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025)
Y. Yang, P. Carlson, Y. Qiao, W. Xie, S. He and T. Yang, LSTM-based Selective Dense Text Retrieval Guided by Sparse Lexical Retrieval. Proc. of 2025 European Conference on Information Retrieval (ECIR 2025).
S. He, M. Al-Darabsah, S. Nair, J. May, T. Agarwal, T. Yang and C. Hui Teo. Token Pruning Optimization for Efficient Dense Retrieval with Multi-Vector Representations Proc. of 2025 European Conference on Information Retrieval (ECIR 2025).
Y. Qiao, P. Carlson, S. He, Y. Yang, T. Yang, Threshold-driven Pruning with Segmented Maximum Term Weights for Approximate Cluster-based Sparse Retrieval. EMNLP 2024 (2024 Conference on Empirical Methods in Natural Language Processing). Outsanding paper award. An earlier version appeared in axXiv 2404.08896 April 2024
Y. Yang, S. He, T. Yang, On Adaptive Knowledge Distillation with Generalized KL-Divergence Loss for Ranking Model Refinement. ICTIR 2024 (10th ACM SIGIR/14th International Conference on the Theory of Information Retrieval)
Y. Yang, Y. Qiao, S. He and T. Yang, Weighted KL-Divergence for Document Ranking Model Refinement. SIGIR 2024 (47th International ACM SIGIR Conference on Research and Development in Information Retrieval)
Y. Yang, P. Carlson, S. He, Y. Qiao and T. Yang, Cluster-based Partial Dense Retrieval Fused with Sparse Text Retrieval. SIGIR 2024 (47th International ACM SIGIR Conference on Research and Development in Information Retrieval)
Y. Qiao, S. Ji, C. Wang, J. Shao, T. Yang. Privacy-aware Document Retrieval with Two-level Inverted Indexing Information Retrieval Journal. No. 12, Nov 2023. PDF
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).

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.

Efficient Neural Document Ranking with Compact Representations