ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction

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Transformers: State-of-the-Art Natural Language Processing

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Product Quantization for Nearest Neighbor Search

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HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

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TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

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FEVER: a Large-scale Dataset for Fact Extraction and VERification

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ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT

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MS MARCO: A Human Generated MAchine Reading COmprehension DatasetPreprint

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Latent retrieval for weakly supervised open domain question answering

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MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers

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Passage Re-ranking with BERT

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REALM: Retrieval-Augmented Language Model Pre-Training

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SPECTER: Document-level Representation Learning using Citation-informed Transformers

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RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering

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SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking

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Fact or Fiction: Verifying Scientific Claims

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Improving language models by retrieving from trillions of tokens

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Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

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Sparse, Dense, and Attentional Representations for Text Retrieval

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Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

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A Full-Text Learning to Rank Dataset for Medical Information Retrieval

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Optimizing Dense Retrieval Model Training with Hard Negatives

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Unsupervised Corpus Aware Language Model Pre-training for Dense Passage Retrieval

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Optimizing Dense Retrieval Model Training with Hard Negatives

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COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted List

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Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

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Poly-encoders: Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring

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AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training

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RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking

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Learning Passage Impacts for Inverted Indexes

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A Few Brief Notes on DeepImpact, COIL, and a Conceptual Framework for Information Retrieval TechniquesPreprint

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SPLADE v2: Sparse Lexical and Expansion Model for Information RetrievalPreprint

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Context-Aware Term Weighting For First Stage Passage Retrieval

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Efficient Document Re-Ranking for Transformers by Precomputing Term Representations

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RepBERT: Contextualized Text Embeddings for First-Stage RetrievalPreprint

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HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification

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Advances in residual vector quantization: a review

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Retrieval of the Best Counterargument without Prior Topic Knowledge

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Distilling Dense Representations for Ranking using Tightly-Coupled TeachersPreprint

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Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance

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CLIMATE-FEVER: A Dataset for Verification of Real-World Climate ClaimsPreprint

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Learning Dense Representations of Phrases at Scale

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Relevance-guided Supervision for OpenQA with ColBERT

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Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval

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Efficient Passage Retrieval with Hashing for Open-domain Question Answering

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TREC-COVID: Constructing a Pandemic Information Retrieval Test CollectionPreprint

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RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question AnsweringPreprint

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Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge DistillationPreprint

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PAIR: Leveraging Passage-Centric Similarity Relation for Improving Dense Passage Retrieval

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Modularized Transfomer-based Ranking Framework

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Domain-matched Pre-training Tasks for Dense Retrieval

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Projected Residual Vector Quantization for ANN Search

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Phrase Retrieval Learns Passage Retrieval, Too

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GooAQ: Open Question Answering with Diverse Answer Types

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On Approximate Nearest Neighbour Selection for Multi-Stage Dense Retrieval

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TRQ: Ternary Neural Networks With Residual Quantization

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A Memory Efficient Baseline for Open Domain Question AnsweringPreprint

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A Double Residual Compression Algorithm for Efficient Distributed LearningPreprint

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Learning To Retrieve: How to Train a Dense Retrieval Model Effectively and EfficientlyPreprint

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Optimized residual vector quantization for efficient approximate nearest neighbor search

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Zero-Shot Dense Retrieval with Momentum Adversarial Domain Invariant Representations

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Hindsight: Posterior-guided training of retrievers for improved open-ended generationPreprint

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Residual Quantization for Low Bit-Width Neural Networks

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Baleen: Robust Multi-Hop Reasoning at Scale via Condensed RetrievalPreprint

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SPLADE: Sparse Lexical and Expansion Model for First Stage RankingPreprint

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Multi-Vector Attention Models for Deep Re-ranking

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SDR: Efficient Neural Re-ranking using Succinct Document Representation

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Dense Text Retrieval Based on Pretrained Language Models: A Survey

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Retrieval-augmented generation for educational application: A systematic survey

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From Distillation to Hard Negative Sampling

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ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems

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RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder

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DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines

Khattab, O., Singhvi, A., Maheshwari, P., Zhang, Z., Santhanam, K., Vardhamanan, S., Haq, S., Sharma, A., Joshi, T. T., Moazam, H., et al. (2023) · arXiv · doi:10.48550/arxiv.2310.03714 · Cited by 60 · see citing works

MIRACL : A Multilingual Retrieval Dataset Covering 18 Diverse Languages

Zhang, X., Thakur, N., Ogundepo, O., Kamalloo, E., Alfonso-Hermelo, D., Li, X., Liu, Q., Rezagholizadeh, M., & Lin, J. (2023) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00595 · Cited by 63 · see citing works

CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing

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Efficient Inverted Indexes for Approximate Retrieval over Learned Sparse Representations

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Extending Context Window of Large Language Models via Positional Interpolation

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How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense Retrieval

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Context-faithful Prompting for Large Language Models

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SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval

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When Language Model Meets Private Library

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A Review of AI-Driven Automation Technologies: Latest Taxonomies, Existing Challenges, and Future Prospects

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Answering Questions by Meta-Reasoning over Multiple Chains of Thought

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Practical and Asymptotically Optimal Quantization of High-Dimensional Vectors in Euclidean Space for Approximate Nearest Neighbor Search

Gao, J., Gou, Y., Xu, Y., Yang, Y., Long, C., & Wong, R. C.-W. (2025) · Proceedings of the ACM on Management of Data · doi:10.1145/3725413 · Cited by 38 · see citing works

Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models

Nair, S., Yang, E., Lawrie, D., Duh, K., McNamee, P., Murray, K., Mayfield, J., & Oard, D. W. (2022) · Lecture notes in computer science · doi:10.1007/978-3-030-99736-6_26 · Cited by 36 · see citing works

Query Performance Prediction for Neural IR: Are We There Yet?

Faggioli, G., Formal, T., Marchesin, S., Clinchant, S., Ferro, N., & Piwowarski, B. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-28244-7_15 · Cited by 34 · see citing works

ConTextual Masked Auto-Encoder for Dense Passage Retrieval

Wu, D. D., Ma, G., Lin, M. S., Lin, Z., Wang, Z., & Hu, S. (2023) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v37i4.25598 · Cited by 39 · see citing works

Scaling Laws For Dense Retrieval

Fang, Y., Zhan, J., Ai, Q., Mao, J., Su, W., Chen, J., & Liu, Y. (2024) · Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3626772.3657743 · Cited by 28 · see citing works

UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of Rerankers

Saad-Falcon, J., Khattab, O., Santhanam, K., Florian, R., Franz, M., Roukos, S., Sil, A., Sultan, M. A., & Potts, C. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.693 · Cited by 38 · see citing works

Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators

Liang, C., Deng, Y., Bian, Y., Qin, Z., Wu, B., Chua, T., & Wong, K. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.390 · Cited by 34 · see citing works

Soft prompt tuning for augmenting dense retrieval with large language models

Peng, Z., Wu, X., Wang, Q., & Fang, Y. (2024) · Knowledge-Based Systems · doi:10.1016/j.knosys.2024.112758 · Cited by 36 · see citing works

Dual retrieving and ranking medical large language model with retrieval augmented generation

Yang, Q., Zuo, H., Su, R., Su, H., Zeng, T., Zhou, H., Wang, R., Chen, J., Lin, Y., Chen, Z., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-00724-w · Cited by 26 · see citing works

A Symmetric Dual Encoding Dense Retrieval Framework for Knowledge-Intensive Visual Question Answering

Salemi, A., Pizzorno, J. A., & Zamani, H. (2023) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3539618.3591629 · Cited by 27 · see citing works

Towards Effective and Efficient Sparse Neural Information Retrieval

Formal, T., Lassance, C., Piwowarski, B., & Clinchant, S. (2023) · ACM Transactions on Information Systems · doi:10.1145/3634912 · Cited by 25 · see citing works

TravelRAG: A Tourist Attraction Retrieval Framework Based on Multi-Layer Knowledge Graph

Song, S., Yang, C., Li, X., Shang, H., Li, Z., & Chang, Y. (2024) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi13110414 · Cited by 25 · see citing works

FRCL-MNER: A Finer Grained Rank-Based Contrastive Learning Framework for Multimodal NER

Yan, T., Zhao, S., Ma, W., Song, S., Wang, C., Rao, Z., Chen, S., Luo, Z., & Liu, X. (2025) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2025.3528567 · Cited by 23 · see citing works

PROD: Progressive Distillation for Dense Retrieval

Lin, Z., Gong, Y., Liu, X., Zhang, H., Lin, C., Dong, A., Jiao, J., Lu, J., Jiang, D., Majumder, R., et al. (2023) · International World Wide Web Conference (WWW) · doi:10.1145/3543507.3583421 · Cited by 26 · see citing works

HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models

Gutiérrez, B. J., Shu, Y., Gu, Y., Yasunaga, M., & Su, Y. (2024) · arXiv · doi:10.48550/arxiv.2405.14831 · Cited by 152 · see citing works

Correctness is not Faithfulness in Retrieval Augmented Generation Attributions

Wallat, J., Heuss, M., Rijke, M. D., & Anand, A. (2025) · Proceedings of the 2025 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval (ICTIR) · doi:10.1145/3731120.3744592 · Cited by 21 · see citing works

Towards Query Performance Prediction for Neural Information Retrieval: Challenges and Opportunities

Faggioli, G., Formal, T., Lupart, S., Marchesin, S., Clinchant, S., Ferro, N., & Piwowarski, B. (2023) · ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR) · doi:10.1145/3578337.3605142 · Cited by 21 · see citing works

Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language Models

Salemi, A., & Zamani, H. (2024) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3626772.3657733 · Cited by 22 · see citing works

A Dense Representation Framework for Lexical and Semantic Matching

Lin, S.-C., & Lin, J. (2023) · ACM Transactions on Information Systems · doi:10.1145/3582426 · Cited by 23 · see citing works

Parameter-Efficient Prompt Tuning Makes Generalized and Calibrated Neural Text Retrievers

Tam, W., Liu, X., Ji, K., Xue, L., Liu, J., Li, T., Dong, Y., & Tang, J. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.874 · Cited by 20 · see citing works

Fine-Grained Distillation for Long Document Retrieval

Zhou, Y., Shen, T., Geng, X., Tao, C., Shen, J., Long, G., Xu, C., & Jiang, D. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i17.29947 · Cited by 21 · see citing works

Learning Retrieval Augmentation for Personalized Dialogue Generation

Huang, Q., Fu, S., Liu, X., Wang, W., Ko, T., Zhang, Y., & Tang, L. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.154 · Cited by 16 · see citing works

Scaling Sparse and Dense Retrieval in Decoder-Only LLMs

Zeng, H., Killingback, J., & Zamani, H. (2025) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3726302.3730225 · Cited by 15 · see citing works

Zero-shot Query Contextualization for Conversational Search

Krasakis, A. M., Yates, A., & Kanoulas, E. (2022) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3477495.3531769 · Cited by 17 · see citing works

SpaDE

Choi, E., Lee, S., Choi, M., Ko, H., Song, Y.-I., & Lee, J. (2022) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3511808.3557456 · Cited by 17 · see citing works

Translate-Distill: Learning Cross-Language Dense Retrieval by Translation and Distillation

Yang, E., Lawrie, D., Mayfield, J., Oard, D. W., & Miller, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-56060-6_4 · Cited by 18 · see citing works

Efficient Multi-vector Dense Retrieval with Bit Vectors

Nardini, F. M., Rulli, C., & Venturini, R. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-56060-6_1 · Cited by 16 · see citing works

A Reproducibility Study of PLAID

MacAvaney, S., & Tonellotto, N. (2024) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3626772.3657856 · Cited by 15 · see citing works

SLIM: Sparsified Late Interaction for Multi-Vector Retrieval with Inverted Indexes

Li, M., Lin, S.-C., Ma, X., & Lin, J. (2023) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3539618.3591977 · Cited by 15 · see citing works

Retrieval as Attention: End-to-end Learning of Retrieval and Reading within a Single Transformer

Jiang, Z., Gao, L., Wang, Z., Araki, J., Ding, H., Callan, J., & Neubig, G. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.149 · Cited by 22 · see citing works

RecJPQ: Training Large-Catalogue Sequential Recommenders

Petrov, A. V., & Macdonald, C. (2024) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3616855.3635821 · Cited by 17 · see citing works

Evaluating Token-Level and Passage-Level Dense Retrieval Models for Math Information Retrieval

Zhong, W., Yang, J.-H., Xie, Y., & Lin, J. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.78 · Cited by 17 · see citing works

DMDD: A Large-Scale Dataset for Dataset Mentions Detection

Pan, H., Zhang, Q., Dragut, E. C., Caragea, C., & Latecki, L. J. (2023) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00592 · Cited by 14 · see citing works

Pairing Clustered Inverted Indexes with κ-NN Graphs for Fast Approximate Retrieval over Learned Sparse Representations

Bruch, S., Nardini, F. M., Rulli, C., & Venturini, R. (2024) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3627673.3679977 · Cited by 16 · see citing works

Finding environmental-friendly chemical synthesis with AI and high-throughput robotics

Hao, V. V., Bui, K.-H., Khoa, D. D. D., Duong-Tuan, M., Le, D. D., & Nguyen-Dang, T. (2024) · Journal of Science Advanced Materials and Devices · doi:10.1016/j.jsamd.2024.100818 · Cited by 13 · see citing works

M3DocVQA: Multi-Modal Multi-Page Multi-Document Understanding

Cho, J., Mahata, D., İrsoy, O., He, Y., & Bansal, M. (2025) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw69036.2025.00649 · Cited by 13 · see citing works

Representation Sparsification with Hybrid Thresholding for Fast SPLADE-based Document Retrieval

Qiao, Y., Yang, Y., He, S., & Yang, T. (2023) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3539618.3592051 · Cited by 12 · see citing works

Soft Prompt Decoding for Multilingual Dense Retrieval

Huang, Z., Zeng, H., Zamani, H., & Allan, J. (2023) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3539618.3591769 · Cited by 13 · see citing works

LI-RAGE: Late Interaction Retrieval Augmented Generation with Explicit Signals for Open-Domain Table Question Answering

Lin, W., Blloshmi, R., Byrne, B., de Gispert, A., & Iglesias, G. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-short.133 · Cited by 11 · see citing works

Learned Token Pruning in Contextualized Late Interaction over BERT (ColBERT)

Lassance, C., Maachou, M., Park, J., & Clinchant, S. (2022) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3477495.3531835 · Cited by 12 · see citing works

CITADEL: Conditional Token Interaction via Dynamic Lexical Routing for Efficient and Effective Multi-Vector Retrieval

Li, M., Lin, S.-C., Oğuz, B., Ghoshal, A., Lin, J., Mehdad, Y., Yih, W.-T., & Chen, X. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.663 · Cited by 19 · see citing works

SiReRAG: Indexing Similar and Related Information for Multihop ReasoningPreprint

Zhang, N., Choubey, P. K., Fabbri, A. R., Bernadett-Shapiro, G., Zhang, R., Mitra, P., Xiong, C., & Wu, C.-S. (2024) · Qeios · doi:10.32388/93o2s3 · Cited by 17 · see citing works

An Experimental Study on Pretraining Transformers from Scratch for IR

Lassance, C., Déjean, H., & Clinchant, S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-28244-7_32 · Cited by 10 · see citing works

Toward Privacy-preserving Text Embedding Similarity with Homomorphic Encryption

Kim, D., Lee, G., & Oh, S. (2022) · Workshop on Financial Technology and Natural Language Processing (FinNLP) · doi:10.18653/v1/2022.finnlp-1.4 · Cited by 10 · see citing works

Adapting Standard Retrieval Benchmarks to Evaluate Generated Answers

Arabzadeh, N., Bigdeli, A., & Clarke, C. L. A. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-56060-6_26 · Cited by 15 · see citing works

Private-library-oriented code generation with large language models

Zan, D., Chen, B., Gong, Y., Cao, J., Zhang, F., Wu, B., Guan, B., Yin, Y., & Wang, Y. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.113934 · Cited by 29 · see citing works

Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking

Santhanam, K., Saad-Falcon, J., Franz, M., Khattab, O., Sil, A., Florian, R., Sultan, M. A., Roukos, S., Zaharia, M., & Potts, C. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.738 · Cited by 10 · see citing works

Bridging the gap: A survey of document retrieval techniques for high-resource and low-resource languages

Kazi, S., Khoja, S., & Daud, A. (2025) · Computer Science Review · doi:10.1016/j.cosrev.2025.100756 · Cited by 9 · see citing works

Joint Optimization of Multi-vector Representation with Product Quantization

Fang, Y., Zhan, J., Liu, Y., Mao, J., Zhang, M., & Ma, S. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-17120-8_49 · Cited by 9 · see citing works

Improving RAG Quality for Large Language Models with Topic-Enhanced Reranking

Ampazis, N. (2024) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-63215-0_6 · Cited by 10 · see citing works

Systematic Evaluation of Neural Retrieval Models on the Touché 2020 Argument Retrieval Subset of BEIR

Thakur, N., Bonifacio, L., Fröbe, M., Bondarenko, A., Kamalloo, E., Potthast, M., Hagen, M., & Lin, J. (2024) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3626772.3657861 · Cited by 9 · see citing works

Investigating the Scalability of Approximate Sparse Retrieval Algorithms to Massive Datasets

Bruch, S., Nardini, F. M., Rulli, C., Venturini, R., & Venuta, L. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-88714-7_43 · Cited by 12 · see citing works

Efficient Constant-Space Multi-vector Retrieval

MacAvaney, S., Mallia, A., & Tonellotto, N. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-88714-7_22 · Cited by 10 · see citing works

Efficient Re-ranking with Cross-encoders via Early Exit

Busolin, F., Lucchese, C., Nardini, F. M., Orlando, S., Perego, R., Trani, S., & Veneri, A. (2025) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3726302.3729962 · Cited by 9 · see citing works

W-RAG: Weakly Supervised Dense Retrieval in RAG for Open-domain Question Answering

Nian, J., Peng, Z., Wang, Q., & Fang, Y. (2025) · ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR) · doi:10.1145/3731120.3744578 · Cited by 12 · see citing works

Evaluating Retrieval Augmented Generation-enhanced Large Language Models for Question Answering On German Neurovascular Guidelines

Vach, M., Gliem, M., Weiss, D., Ivan, V. L., Hauke, F., Boschenriedter, C., Rubbert, C., & Caspers, J. (2025) · Clinical Neuroradiology · doi:10.1007/s00062-025-01562-z · Cited by 9 · see citing works

Attacking Open-domain Question Answering by Injecting Misinformation

Pan, L., Chen, W., Kan, M.-Y., & Wang, W. Y. (2023) · Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.18653/v1/2023.ijcnlp-main.35 · Cited by 9 · see citing works

Data Augmentation and Large Language Model for Legal Case Retrieval and Entailment

Bui, M.-Q., Do, D.-T., Le, N.-K., Nguyen, D.-H., Nguyen, K.-V.-H., Anh, T. P. N., & Nguyen, L.-M. (2024) · The Review of Socionetwork Strategies · doi:10.1007/s12626-024-00158-2 · Cited by 11 · see citing works

One Blade for One Purpose: Advancing Math Information Retrieval using Hybrid Search

Zhong, W., Lin, S.-C., Yang, J.-H., & Lin, J. (2023) · Annual International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3539618.3591746 · Cited by 14 · see citing works

Exploring Dense Retrieval for Dialogue Response Selection

Lan, T., Cai, D., Wang, Y., Su, Y., Huang, H., & Mao, X.-L. (2023) · ACM Transactions on Information Systems · doi:10.1145/3632750 · Cited by 10 · see citing works

Incorporating Verification Standards for Security Requirements Generation from Functional Specifications

Lian, X., Wang, S., Zou, H., Liu, F., Wu, J., & Zhang, L. (2025) · Proceedings of the ACM on software engineering. · doi:10.1145/3729347 · Cited by 8 · see citing works

WARP: An Efficient Engine for Multi-Vector Retrieval

Scheerer, J. L., Zaharia, M., Potts, C., Alonso, G., & Khattab, O. (2025) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3726302.3729904 · Cited by 8 · see citing works

LLM-augmented multi-agent cooperative framework for medical case retrieval in cardiology

Deng, L., Hu, H., Lu, K., & He, P. (2025) · Journal of King Saud University Computer and Information Sciences · doi:10.1007/s44443-025-00311-z · Cited by 8 · see citing works

CoSPLADE: Contextualizing SPLADE for Conversational Information Retrieval

Le, N. H., Gerald, T., Formal, T., Nie, J., Piwowarski, B., & Soulier, L. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-28244-7_34 · Cited by 8 · see citing works

RetroMAE-2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models

Liu, Z., Xiao, S., Shao, Y., & Cao, Z. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.148 · Cited by 15 · see citing works

I3 Retriever: Incorporating Implicit Interaction in Pre-trained Language Models for Passage Retrieval

Dong, Q., Liu, Y., Ai, Q., Li, H., Wang, S., Liu, Y., Yin, D., & Ma, S. (2023) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3583780.3614923 · Cited by 10 · see citing works

Improving First-stage Retrieval of Point-of-interest Search by Pre-training Models

Mei, L., Mao, J., Hu, J., Tan, N., Chai, H., & Wen, J.-R. (2023) · ACM Transactions on Information Systems · doi:10.1145/3631937 · Cited by 8 · see citing works

TriSampler: A Better Negative Sampling Principle for Dense Retrieval

Zhen, Y., Shao, Z., Dong, Y., & Tang, J. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i8.28779 · Cited by 10 · see citing works

Enhancing Large Language Models Through External Domain Knowledge

Welz, L., & Lanquillon, C. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-60615-1_9 · Cited by 8 · see citing works

HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights

Gökdemir, O., Siebenschuh, C., Brace, A., Wells, A. I., Hsu, B., Hippe, K., Setty, P. V., Ajith, A., Pauloski, J. G., Sastry, V. K., et al. (2025) · Platform for Advanced Scientific Computing Conference (PASC) · doi:10.1145/3732775.3733586 · Cited by 11 · see citing works

Stochastic Retrieval-Conditioned Reranking

Zamani, H., Bendersky, M., Metzler, D., Zhuang, H., & Wang, X. (2022) · ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR) · doi:10.1145/3539813.3545141 · Cited by 8 · see citing works

Learning Multi-Stage Multi-Grained Semantic Embeddings for E-Commerce Search

Wang, B., Li, M., Zeng, Z., Zhuo, J., Wang, S., Xu, S., Long, B., & Yan, W. (2023) · International World Wide Web Conference (WWW) · doi:10.1145/3543873.3584638 · Cited by 8 · see citing works

Predictive Uncertainty-based Bias Mitigation in Ranking

Heuss, M., Cohen, D., Mansoury, M., de Rijke, M., & Eickhoff, C. (2023) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3583780.3615011 · Cited by 10 · see citing works

Distillation for Multilingual Information Retrieval

Yang, E., Lawrie, D., & Mayfield, J. (2024) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3626772.3657955 · Cited by 8 · see citing works

Effective Inference-Free Retrieval for Learned Sparse Representations

Nardini, F. M., Nguyen, T. D.-M., Rulli, C., Venturini, R., & Yates, A. (2025) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3726302.3730185 · Cited by 7 · see citing works

Hypencoder: Hypernetworks for Information Retrieval

Killingback, J., Zeng, H., & Zamani, H. (2025) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3726302.3729983 · Cited by 8 · see citing works

Expert-level policy style measurement via knowledge distillation with large language model collaboration

Zhang, Y., Huang, B., Yuan, W., Jiang, Z., Peng, L., Chen, S., & Tan‐Soo, J. (2025) · Information Processing & Management · doi:10.1016/j.ipm.2025.104090 · Cited by 7 · see citing works

Dense Retrieval with Entity Views

Tran, H. D., & Yates, A. (2022) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3511808.3557285 · Cited by 7 · see citing works

Multivariate Representation Learning for Information Retrieval

Zamani, H., & Bendersky, M. (2023) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3539618.3591740 · Cited by 7 · see citing works

MASTER: Multi-task Pre-trained Bottlenecked Masked Autoencoders Are Better Dense Retrievers

Zhou, K., Liu, X., Gong, Y., Zhao, W. X., Jiang, D., Duan, N., & Wen, J.-R. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-43415-0_37 · Cited by 13 · see citing works

Towards a Unified Framework for Reference Retrieval and Related Work Generation

Shi, Z., Gao, S., Zhang, Z., Chen, X., Chen, Z., Ren, P., & Ren, Z. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.385 · Cited by 8 · see citing works

GLEN: Generative Retrieval via Lexical Index Learning

Lee, S., Choi, M., & Lee, J. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.477 · Cited by 10 · see citing works

Jina-ColBERT-v2: A General-Purpose Multilingual Late Interaction Retriever

Xiao, H., Wang, B., & Jha, R. (2024) · Workshop on Multilingual Representation Learning (MRL) · doi:10.18653/v1/2024.mrl-1.11 · Cited by 7 · see citing works

SPLATE: Sparse Late Interaction Retrieval

Formal, T., Clinchant, S., Déjean, H., & Lassance, C. (2024) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3626772.3657968 · Cited by 10 · see citing works

PLAID: An Efficient Engine for Late Interaction RetrievalPreprint

Santhanam, K., Khattab, O., Potts, C., & Zaharia, M. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2205.09707 · Cited by 10 · see citing works

QuadrupletBERT: An Efficient Model For Embedding-Based Large-Scale Retrieval

Liu, P., Wang, S., Wang, X., Ye, W., & Zhang, S. (2021) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2021.naacl-main.292 · Cited by 10 · see citing works

ColMate: Contrastive Late Interaction and Masked Text for Multimodal Document Retrieval

Masry, A., Thakkar, M., Bechard, P., Madhusudhan, S. T., Awal, R., Mishra, S., Suresh, A. K., Daruru, S., Hoque, E., Gella, S., et al. (2025) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2025.emnlp-industry.145 · Cited by 2 · see citing works