Siamese Retrieval Models
Siamese Retrieval Models is a retrieval framework that employs a twin neural network architecture to jointly encode query and document representations into a shared semantic space, enabling similarity-based ranking through symmetric parameter sharing and distance metric learning.
22
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1.5K
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85
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48
Institutions
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2017–2026
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Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
Lee Xiong, Chenyan Xiong, Ye Li et al. · arXiv (Cornell University) · 2020 · 230 citations · Full text
Sketch-based image retrieval via Siamese convolutional neural network
Yonggang Qi, Yi-Zhe Song, Honggang Zhang et al. · 2016 · 222 citations
Towards Accurate Duplicate Bug Retrieval Using Deep Learning Techniques
Jayati Deshmukh, K. M. Annervaz, Sanjay Podder et al. · 2017 · 102 citations
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Microsoft Research (United Kingdom)
Cambridge, United Kingdom
3 h-index
15 publications
2.9K citations
Qilu University of Technology
Jinan, China
2 h-index
4 publications
155 citations
Shandong Academy of Sciences
Jinan, China
2 h-index
4 publications
155 citations
Shiraz University of Technology
Shiraz, Iran
1 h-index
2 publications
60 citations
Microsoft (India)
Hyderabad, India
1 h-index
1 publications
79 citations
Albert Einstein College of Medicine
Bronx, United States
1 h-index
1 publications
50 citations
Hangzhou Dianzi University
Hangzhou, China
1 h-index
1 publications
11 citations
RWTH Aachen University
Aachen, Germany
1 h-index
3 publications
36 citations
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Repository · 3 publications · 299 citations
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1 publications · 48 citations
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1 publications · 13 citations
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1 publications · 11 citations
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1 publications · 30 citations
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