Billion-Scale Similarity Search with GPUs

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155

Distributed Representations of Words and Phrases and their Compositionality

Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1310.4546 · Cited by 24,533

Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Han, S., Mao, H., & Dally, W. J. (2015) · arXiv · doi:10.48550/arxiv.1510.00149 · Cited by 4,662

Bag of Tricks for Efficient Text Classification

Joulin, A., Grave, E., Bojanowski, P., & Mikolov, T. (2017) · Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers · doi:10.18653/v1/e17-2068 · Cited by 4,545

CNN Features Off-the-Shelf: An Astounding Baseline for Recognition

Razavian, A. S., Azizpour, H., Sullivan, J., & Carlsson, S. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvprw.2014.131 · Cited by 4,451

Product Quantization for Nearest Neighbor Search

Jégou, H., Douze, M., & Schmid, C. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.57 · Cited by 2,956 · cited 5×

Untitled work

Williams, S., Waterman, A., & Patterson, D. A. (2009) · Communications of the ACM · doi:10.1145/1498765.1498785 · Cited by 2,798

Deep Clustering for Unsupervised Learning of Visual Features

Caron, M., Bojanowski, P., Joulin, A., & Douze, M. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01264-9_9 · Cited by 2,674

Sorting networks and their applications

Batcher, K. E. (1968) · doi:10.1145/1468075.1468121 · Cited by 2,442

BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs

Yang, Z., Huang, T., Ding, M., Dong, Y., Ying, R., Cen, Y., Geng, Y., & Tang, J. (2023) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3580305.3599263 · Cited by 14

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 38

Saving Dense Retriever from Shortcut Dependency in Conversational Search

Kim, S., & Kim, G. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.701 · Cited by 21

DAQAS: Deep Arabic Question Answering System based on duplicate question detection and machine reading comprehension

Alami, H., Mahdaouy, A. E., Benlahbib, A., En-Nahnahi, N., Berrada, I., & Alaoui, S. O. E. (2023) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2023.101709 · Cited by 15

Autonomous GPU-based UAS for inspection of confined spaces: Application to marine vessel classification

Brogaard, R. Y., & Boukas, E. (2023) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2023.104590 · Cited by 14

Enhancing Video Retrieval with Robust CLIP-Based Multimodal System

Le-Quynh, M.-D., Nguyen, A.-T., Quang-Hoang, A.-T., Dinh, V.-H., Nguyen, T.-H., Ngo, H.-B., & An, M.-H. (2023) · International Symposium on Information and Communication Technology · doi:10.1145/3628797.3629011 · Cited by 14

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 26

Experimental Analysis of Large-Scale Learnable Vector Storage Compression

Zhang, H., Zhao, P., Miao, X., Shao, Y., Liu, Z., Yang, T., & Cui, B. (2023) · Proceedings of the VLDB Endowment · doi:10.14778/3636218.3636234 · Cited by 17

Retrieval Augmented Generation with Rich Answer Encoding

Huang, W., Lapata, M., Vougiouklis, P., Papasarantopoulos, N., & Pan, J. Z. (2023) · International Joint Conference on Natural Language Processing and Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL) · doi:10.18653/v1/2023.ijcnlp-main.65 · Cited by 19

FOSSIL: Free Open-Vocabulary Semantic Segmentation through Synthetic References Retrieval

Barsellotti, L., Amoroso, R., Baraldi, L., & Cucchiara, R. (2024) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv57701.2024.00149 · Cited by 20

Contextualizing Internet Memes Across Social Media Platforms

Joshi, S., Ilievski, F., & Luceri, L. (2024) · International World Wide Web Conference (WWW) · doi:10.1145/3589335.3651970 · Cited by 24

Memory-Scalable and Simplified Functional Map Learning

Magnet, R., & Ovsjanikov, M. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.00387 · Cited by 14

A Practical Application of Retrieval-Augmented Generation for Website-Based Chatbots: Combining Web Scraping, Vectorization, and Semantic Search

Pokhrel, S., Bina, K. C., & Shah, P. B. (2025) · Journal of Trends in Computer Science and Smart Technology · doi:10.36548/jtcsst.2024.4.007 · Cited by 17

Answering Binary Causal Questions: A Transfer Learning Based Approach

Kayesh, H., Islam, M. S., Wang, J., Anirban, S., Kayes, A. S. M., & Watters, P. (2020) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn48605.2020.9207662 · Cited by 14

Engaging Politically Diverse Audiences on Social Media

Saveski, M., Beeferman, D., McClure, D., & Roy, D. K. (2022) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v16i1.19342 · Cited by 15

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper)

Peng, H., Chen, S., Wang, Z., Yang, J., Weitze, S., Geng, T., Li, A., Bi, J., Song, M., Jiang, W., et al. (2021) · doi:10.1109/iccad51958.2021.9643528 · Cited by 14

Question answering with deep neural networks for semi-structured heterogeneous genealogical knowledge graphs

Suissa, O., Zhitomirsky‐Geffet, M., & Elmalech, A. (2022) · Semantic Web · doi:10.3233/sw-222925 · Cited by 14

Accelerating the Inference of the Exa.TrkX Pipeline

Lazar, A., Ju, X., Murnane, D., Calafiura, P., Farrell, S., Xu, Y., Spiropulu, M., Vlimant, J.-R., Cerati, G., Gray, L., et al. (2023) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2438/1/012008 · Cited by 14

LANNS

Doshi, I., Das, D., Bhutani, A., Kumar, R., Bhatt, R., & Balasubramanian, N. (2021) · Proceedings of the VLDB Endowment · doi:10.14778/3503585.3503594 · Cited by 14

Efficient exact K-nearest neighbor graph construction for billion-scale datasets using GPUs with tensor cores

Ji, Z.-R., & Wang, C.-L. (2022) · International Conference on Supercomputing · doi:10.1145/3524059.3532368 · Cited by 14

Building and Deploying a Multi-Stage Recommender System with Merlin

Higley, K., Oldridge, E., Ak, R., Rabhi, S., & Moreira, G. D. S. P. (2022) · ACM Conference on Recommender Systems (RecSys) · doi:10.1145/3523227.3551468 · Cited by 14

Semisupervised Machine Learning for Sensitive Open Modification Spectral Library Searching

Arab, I., Fondrie, W. E., Laukens, K., & Bittremieux, W. (2023) · Journal of Proteome Research · doi:10.1021/acs.jproteome.2c00616 · Cited by 14

Reasoning over Public and Private Data in Retrieval-Based Systems

Arora, S., Lewis, P., Fan, A., Kahn, J., & Ré, C. (2023) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00580 · Cited by 18

Dictionary-based Data Augmentation for Cross-Domain Neural Machine TranslationPreprint

Peng, W., Huang, C., Li, T., Chen, Y., & Liu, Q. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2004.02577 · Cited by 27

End-to-End QA on COVID-19: Domain Adaptation with Synthetic TrainingPreprint

Reddy, R. G., Iyer, B., Sultan, M. A., Zhang, R., Sil, A., Castelli, V., Florian, R., & Roukos, S. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2012.01414 · Cited by 20

Results of the NeurIPS'21 Challenge on Billion-Scale Approximate Nearest Neighbor SearchPreprint

Simhadri, H. V., Williams, G., Aumüller, M., Douze, M., Babenko, A., Baranchuk, D., Chen, Q., Hosseini, L., Krishnaswamy, R., Srinivasa, G., et al. (2022) · arXiv (Cornell University) · doi:10.48550/arxiv.2205.03763 · Cited by 31

Caching Historical Embeddings in Conversational Search

Frieder, O., Mele, I., Muntean, C. I., Nardini, F. M., Perego, R., & Tonellotto, N. (2022) · ACM Transactions on the Web · doi:10.1145/3578519 · Cited by 13

Learning Balanced Tree Indexes for Large-Scale Vector Retrieval

Li, W., Feng, C., Lian, D., Xie, Y., Liu, H., Ge, Y., & Chen, E. (2023) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3580305.3599406 · Cited by 13

LMCap: Few-shot Multilingual Image Captioning by Retrieval Augmented Language Model Prompting

Ramos, R., Martins, B., & Elliott, D. (2023) · Findings of the Association for Computational Linguistics: ACL (Findings of ACL) · doi:10.18653/v1/2023.findings-acl.104 · Cited by 22

MoralDial: A Framework to Train and Evaluate Moral Dialogue Systems via Moral Discussions

Sun, H., Zhang, Z., Mi, F., Wang, Y., Liu, W., Cui, J., Wang, B., Liu, Q., & Huang, M. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.123 · Cited by 22

Towards Knowledge-Intensive Text-to-SQL Semantic Parsing with Formulaic Knowledge

Dou, L., Gao, Y., Liu, X., Pan, M., Wang, D., Che, W., Zhan, D., Kan, M., & Lou, J. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.350 · Cited by 13

Patent image retrieval using transformer-based deep metric learning

Higuchi, K., & Yanai‬, ‪. (2023) · World Patent Information · doi:10.1016/j.wpi.2023.102217 · Cited by 13

SignQuery: A Natural User Interface and Search Engine for Sign Languages with Wearable Sensors

Zhou, H., Lu, T., Mckinnie, K., Palagano, J., DeHaan, K., & Gowda, M. (2023) · ACM Annual International Conference on Mobile Computing and Networking (MobiCom) · doi:10.1145/3570361.3613286 · Cited by 13

Relative NN-Descent: A Fast Index Construction for Graph-Based Approximate Nearest Neighbor Search

Ono, N., & Matsui, Y. (2023) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3581783.3612290 · Cited by 13

Omni Point: 3D LiDAR-Based Feature Extraction Method for Place Recognition and Point Registration

Im, J.-U., Ki, S.-W., & Won, J. (2024) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2023.3348525 · Cited by 14

Cross-Modal Retrieval for Knowledge-Based Visual Question Answering

Lerner, P., Ferret, O., & Guinaudeau, C. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-56027-9_26 · Cited by 21

FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval

Xu, C., Xu, J., Ding, Y., Zhang, X., & Qi, Q. (2024) · International World Wide Web Conference (WWW) · doi:10.1145/3589334.3645413 · Cited by 13

MeTMaP: Metamorphic Testing for Detecting False Vector Matching Problems in LLM Augmented Generation

Wang, G., Li, Y., Liu, Y., Deng, G., Li, T., Xu, G., Liu, Y., Wang, H., & Wang, K. (2024) · IEEE/ACM International Conference on AI Foundation Models and Software Engineering (FORGE) · doi:10.1145/3650105.3652297 · Cited by 16

VDTuner: Automated Performance Tuning for Vector Data Management Systems

Yang, T., Hu, W., Peng, W., Li, Y., Li, J., Wang, G., & Liu, X. (2024) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde60146.2024.00332 · Cited by 13

PlaceNav: Topological Navigation through Place Recognition

Suomela, L., Kalliola, J., Edelman, H., & Kämäräinen, J. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10610575 · Cited by 13

Leveraging artificial intelligence to identify the psychological factors associated with conspiracy theory beliefs online

Kunst, J. R., Gundersen, A. B., Krysińska, I., Piasecki, J., Wójtowicz, T., Ryguła, R., van der Linden, S., & Morzy, M. (2024) · Nature Communications · doi:10.1038/s41467-024-51740-9 · Cited by 15

Region-Based Representations Revisited

Shlapentokh-Rothman, M., Blume, A., Xiao, Y., Wu, Y., Sethuraman, T. V., Tao, H., Lee, J., Torres, W., Wang, Y.-X., & Hoiem, D. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.01619 · Cited by 19

ViTA: An Efficient Video-to-Text Algorithm using VLM for RAG-based Video Analysis System

Arefeen, M. A., Debnath, B. K., Uddin, M. Y. S., & Chakradhar, S. (2024) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw63382.2024.00232 · Cited by 15

Fine-Tuning Retrieval-Augmented Generation with an Auto-Regressive Language Model for Sentiment Analysis in Financial Reviews

Mathebula, M., Modupe, A., & Marivate, V. N. (2024) · Applied Sciences · doi:10.3390/app142310782 · Cited by 15

AU-RAG: Agent-based Universal Retrieval Augmented Generation

Jang, J., & Li, W.-S. (2024) · Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region (SIGIR-AP) · doi:10.1145/3673791.3698416 · Cited by 22

Cross‐Domain Foundation Model Adaptation: Pioneering Computer Vision Models for Geophysical Data Analysis

Guo, Z., Wu, X., Liang, L., Sheng, H., Chen, N., & Bi, Z. (2025) · Journal of Geophysical Research Machine Learning and Computation · doi:10.1029/2025jh000601 · Cited by 18

PipeRAG: Fast Retrieval-Augmented Generation via Adaptive Pipeline Parallelism

Jiang, W., Zhang, S., Han, B., Wang, J., Wang, B., & Kraska, T. (2025) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3690624.3709194 · Cited by 24

Retrieval-Enhanced Visual Prompt Learning for Few-Shot Classification

Rong, J., Chen, H., Ou, L., Chen, T., Yu, X., & Liu, Y. (2026) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2026.3651774 · Cited by 24

On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks

Mussmann, S., Jia, R., & Liang, P. (2020) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2020.findings-emnlp.305 · Cited by 16

Citation Recommendation for Research Papers via Knowledge Graphs

Brack, A., Hoppe, A., & Ewerth, R. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-86324-1_20 · Cited by 13

Another Look at DPR: Reproduction of Training and Replication of Retrieval

Ma, X., Sun, K., Pradeep, R., Li, M., & Lin, J. (2022) · Lecture notes in computer science · doi:10.1007/978-3-030-99736-6_41 · Cited by 13

An MLP-based Algorithm for Efficient Contrastive Graph Recommendations

Liu, S., Ounis, I., & Macdonald, C. (2022) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3477495.3531874 · Cited by 13

LMFingerprints: Visual Explanations of Language Model Embedding Spaces through Layerwise Contextualization Scores

Sevastjanova, R., Kalouli, A.-L., Beck, C., Hauptmann, H., & El‐Assady, M. (2022) · Computer Graphics Forum · doi:10.1111/cgf.14541 · Cited by 18

Tree Species Classification Based on Self-Supervised Learning with Multisource Remote Sensing Images

Wang, X., Yang, N., Liu, E., Gu, W., Zhang, J., Zhao, S., Sun, G., & Wang, J. (2023) · Applied Sciences · doi:10.3390/app13031928 · Cited by 13

What Are You Token About? Dense Retrieval as Distributions Over the Vocabulary

Ram, O., Bezalel, L., Zicher, A., Belinkov, Y., Berant, J., & Globerson, A. (2023) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2023.acl-long.140 · Cited by 35

Toward Best Practices for Training Multilingual Dense Retrieval Models

Zhang, X., Ogueji, K., Ma, X., & Lin, J. (2023) · ACM Transactions on Information Systems · doi:10.1145/3613447 · Cited by 33

ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning

Shi, Y., Zhou, K., & Liu, N. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-43418-1_7 · Cited by 13

GAUSS-EM, guided accumulation of ultrathin serial sections with a static magnetic field for volume electron microscopy

Fulton, K. A., Watkins, P. V., & Briggman, K. L. (2024) · Cell Reports Methods · doi:10.1016/j.crmeth.2024.100720 · Cited by 12

Unconstrained Foreground Object Search

Zhao, Y., Price, B. L., Cohen, S. D., & Gurari, D. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00212 · Cited by 13

Searching for Embeddings in a Haystack: Link Prediction on Knowledge Graphs with Subgraph Pruning

Joshi, U., & Jacopo Urbani, A. (2020) · International World Wide Web Conference (WWW) · doi:10.1145/3366423.3380043 · Cited by 13

Online multimedia retrieval on CPU–GPU platforms with adaptive work partition

de Souza, R. M., Fernandes, A. G. D. A., Teixeira, T. S. F. X., Teodoro, G., & Ferreira, R. (2020) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2020.10.001 · Cited by 13

Generating Realistic Training Images Based on Tonality-Alignment Generative Adversarial Networks for Hand Pose EstimationPreprint

Chen, L., Lin, S.-Y., Xie, Y., Tang, H., Xue, Y., Xie, X. S., Lin, Y., & Fan, W. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1811.09916 · Cited by 13

RRF102: Meeting the TREC-COVID Challenge with a 100+ Runs EnsemblePreprint

Bendersky, M., Zhuang, H., Ma, J., Han, S., Hall, K., & McDonald, R. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.00200 · Cited by 21

Omni-swarm: A Decentralized Omnidirectional Visual-Inertial-UWB State Estimation System for Aerial Swarm.Preprint

Xu, H., Zhang, Y., Zhou, B., Wang, L., Yao, X., Meng, G., & Shen, S. (2021) · arXiv (Cornell University) · Cited by 13

FreshDiskANN: A Fast and Accurate Graph-Based ANN Index for Streaming Similarity SearchPreprint

Singh, A., Subramanya, S. J., Krishnaswamy, R., & Simhadri, H. V. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.09613 · Cited by 138

Fine-grained knowledge fusion for retrieval-augmented medical visual question answering

Xiao, L., Wang, D., Jing, B., Jiao, Z., Li, R., Liu, R., Miao, Q., & Wang, Q. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103059 · Cited by 12

Phishing email detection using vector similarity search leveraging transformer-based word embedding

Patra, C., Giri, D., Nandi, S., Das, A. K., & Alenazi, M. J. F. (2025) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2025.110403 · Cited by 12

UNIFY: Unified Index for Range Filtered Approximate Nearest Neighbors Search

Liang, A., Zhang, P., Yao, B., Chen, Z., Song, Y., & Cheng, G. (2024) · Proceedings of the VLDB Endowment · doi:10.14778/3717755.3717770 · Cited by 36

A Comprehensive Survey on Retrieval Methods in Recommender Systems

Huang, J., Chen, J., Lin, J., Qin, J., Feng, Z., Zhang, W., & Yu, Y. H. (2025) · ACM Transactions on Information Systems · doi:10.1145/3771925 · Cited by 12

MEMORIA: A Memory Enhancement and MOment RetrIeval Application at the LSC2025

Gago, A., Kaluza, B., & Neves, A. J. R. (2025) · LSC@ICMR · doi:10.1145/3729459.3748693 · Cited by 9

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

Large Scale Question Paraphrase Retrieval with Smoothed Deep Metric Learning

Bonadiman, D., Kumar, A., & Mittal, A. (2019) · Workshop on Noisy User-generated Text (W-NUT) · doi:10.18653/v1/d19-5509 · Cited by 12

RetroNLU: Retrieval Augmented Task-Oriented Semantic Parsing

Gupta, V., Shrivastava, A., Sagar, A., Aghajanyan, A., & Savenkov, D. (2022) · Workshop on NLP for Conversational AI (NLP4ConvAI) · doi:10.18653/v1/2022.nlp4convai-1.15 · Cited by 13

Distilling Knowledge from BERT into Simple Fully Connected Neural Networks for Efficient Vertical Retrieval

Liu, P., Wang, X., Wang, L., Ye, W., Xi, X., & Zhang, S. (2021) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3459637.3481909 · Cited by 14

Machine learning for predicting microfluidic droplet generation properties

Solanki, S. R., Lee, S., Jebakumar, A., Lum, J., Hamidi-Haines, M., Denison, C., Sundheim, M., Schauer, K., Stevenson, P., Hintzman, J., et al. (2022) · Computers & Fluids · doi:10.1016/j.compfluid.2022.105651 · Cited by 13

Joint Global and Dynamic Pseudo Labeling for Semi-Supervised Point Cloud Sequence Segmentation

Liu, J., Chen, Y., Ni, B., & Yu, Z. (2023) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2023.3253210 · Cited by 13

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

Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation

Su, L., Fan, Y. B., Zhu, J., Xiao, X., Duan, H., Zhao, Z., Dong, Z., & Tang, R. (2023) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/3539618.3591643 · Cited by 18

ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop

Zhu, J., Cai, G., Huang, J., Dong, Z., Tang, R., & Zhang, W. (2023) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3580305.3599785 · Cited by 12

Mixed-modality Representation Learning and Pre-training for Joint Table-and-Text Retrieval in OpenQA

Huang, J., Zhong, W., Liu, Q., Gong, M., Jiang, D., & Duan, N. (2022) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2022.findings-emnlp.303 · Cited by 19

Fixing Model Bugs with Natural Language Patches

Murty, S., Manning, C. D., Lundberg, S., & Ribeiro, M. T. (2022) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2022.emnlp-main.797 · Cited by 25

Envisaging a global infrastructure to exploit the potential of digitised collections

Groom, Q., Dillen, M., Addink, W., Ariño, A. H., Bölling, C., Bonnet, P., Cecchi, L., Ellwood, E. R., Figueira, R., Gagnier, P.-Y., et al. (2023) · Biodiversity Data Journal · doi:10.3897/bdj.11.e109439 · Cited by 14

UP-DPC: Ultra-scalable parallel density peak clustering

Ma, L., Yang, G., Yang, Y., Chen, X., Lu, J., Gong, Z., & Hao, Z. (2024) · Information Sciences · doi:10.1016/j.ins.2024.120114 · Cited by 12

Iterative Self-Supervised Learning for Legal Similar Case Retrieval

Liu, Y. A., Tan, T.-P., & Zhan, X. (2024) · IEEE Access · doi:10.1109/access.2024.3358622 · Cited by 12

Personalized Elastic Embedding Learning for On-Device Recommendation

Zheng, R., Qu, L., Chen, T., Zheng, K., Shi, Y., & Yin, H. (2024) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2024.3361562 · Cited by 12

Robust point cloud registration using Hough voting-based correspondence outlier rejection

Han, J.-H., Shin, M., & Paik, J. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.107985 · Cited by 12

DRAM-Based Acceleration of Open Modification Search in Hyperdimensional Space

Kang, J., Xu, W., Bittremieux, W., Moshiri, N., & Simunic, T. (2024) · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · doi:10.1109/tcad.2024.3382842 · Cited by 12

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

Chen, Q., Geng, X., Rosset, C., Buractaon, C., Lu, J., Shen, T., Zhou, K., Xiong, C., Gong, Y., Bennett, P., et al. (2024) · International World Wide Web Conference (WWW) · doi:10.1145/3589335.3648327 · Cited by 16

SGAMF: Sparse Gated Attention-Based Multimodal Fusion Method for Fake News Detection

Du, P., Gao, Y., Li, L., & Li, X. (2024) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2024.3414341 · Cited by 12

Fine-tuning protein embeddings for functional similarity evaluation

Dickson, A. M., & Mofrad, M. R. K. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae445 · Cited by 15

From document-centric to data-centric public service provision

Konstantinidis, I., Kapantai, E., Michailidis, A., Deligiannis, A. P., Berberidis, C., Magnisalis, I. D., & Peristeras, V. (2024) · Digital Government Research and Practice · doi:10.1145/3676279 · Cited by 17

Development of a ChatBot model for health telecare: Integration of LangChain, embeddings with OpenAI, and Pinecone using the question answering technique

Villavicencio, O. E. C., Falconi, S., Tusa, E., & Rodríguez, A. (2024) · Journal of Applied Research and Technology · doi:10.22201/icat.24486736e.2024.22.3.2367 · Cited by 14

Decompose, Enrich, and Extract! Schema-aware Event Extraction using LLMs.

Shiri, F., Moghimifar, F., Haffari, R., Li, Y.-F., Nguyen, V., & Yoo, J. (2024) · International Conference on Information Fusion (FUSION) · doi:10.23919/fusion59988.2024.10706385 · Cited by 23

Automated Radiology Report Labeling in Chest X-Ray Pathologies: Development and Evaluation of a Large Language Model Framework

Abdullah, A., & Kim, S. T. (2025) · JMIR Medical Informatics · doi:10.2196/68618 · Cited by 15

MQRLD: A multimodal data retrieval platform with query-aware feature representation and learned index based on data lake

Sheng, M., Wang, S., Zhang, Y., Wang, K., Wang, J., Luo, Y., & Hao, R. (2025) · Information Processing & Management · doi:10.1016/j.ipm.2025.104101 · Cited by 14

QFAS-KE: Query focused answer summarization using keyword extraction

Goyal, R., Kumar, P., & Singh, V. P. (2025) · Information Processing & Management · doi:10.1016/j.ipm.2025.104104 · Cited by 12

Enhancing nucleotide sequence representations in genomic analysis with contrastive optimization

Refahi, M. S., Sokhansanj, B. A., Mell, J. C., Brown, J. R., Yoo, H., Hearne, G., & ROSEN, G. L. (2025) · Communications Biology · doi:10.1038/s42003-025-07902-6 · Cited by 14

PolyResponse: A Rank-based Approach to Task-Oriented Dialogue with Application in Restaurant Search and Booking

Henderson, M., Vulić, I., Casanueva, I., Budzianowski, P., Gerz, D., Coope, S., Spithourakis, G., Wen, T.-H., Mrkšić, N., & Su, P.-H. (2019) · Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP) · doi:10.18653/v1/d19-3031 · Cited by 13

Optimizing Dense Retrieval Model Training with Hard Negatives

Zhan, J., Mao, J., Liu, Y., Guo, J., Zhang, M., & Ma, S. (2021) · arXiv · doi:10.48550/arxiv.2104.08051 · Cited by 251

Paraphrastic Representations at Scale

Wieting, J., Gimpel, K., Neubig, G., & Berg-kirkpatrick, T. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations · doi:10.18653/v1/2022.emnlp-demos.38 · Cited by 13

IMI-GPU: Inverted multi-index for billion-scale approximate nearest neighbor search with GPUs

Araujo, A., Barreiros, W., Kong, J., Ferreira, R., & Teodoro, G. (2024) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2025.105066

Range query processing on single and multi GPU environments

Barrientos, R. J., Gómez, J. I., Tenllado, C., Prieto, M., & Marı́n, M. (2013) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2013.05.012 · Cited by 7

GPU-Accelerated Algorithms for Graph Vector Search: Taxonomy, Empirical Study, and Research DirectionsPreprint

Liu, Y., Chen, X., Tian, A., Li, H., Li, Q., Zhang, X., Zhou, A., Zhang, C., Li, Q., & Chen, L. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2602.16719

Meeting the challenges of k-nearest neighbor search implementation for GPU accelerators

Hanák, D. (2023) · Digital Repository (National Repository of Grey Literature)

Employing Parallel Architectures in Similarity Search

Kruliš, M. (2013) · Digital Repository (National Repository of Grey Literature)