The Impacts of Data, Ordering, and Intrinsic Dimensionality on Recall in Hierarchical Navigable Small Worlds-Reference-Cited by-同舟云学术

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The Impacts of Data, Ordering, and Intrinsic Dimensionality on Recall in Hierarchical Navigable Small Worlds

Published:2024-08-02 Issue: Volume: Page:25-33
ISSN:
Container-title:Proceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval
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Author:

Elliott Owen P.¹^ORCID,Clark Jesse¹^ORCID

Affiliation:

1. Marqo, Melbourne, VIC, Australia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3664190.3672512

Reference49 articles.

1. [n. d.]. ANNOY library. https://github.com/spotify/annoy Accessed: 2017-08-01.

2. [n. d.]. infgrad/stella-base-en-v2 · Hugging Face - huggingface.co. https: //huggingface.co/infgrad/stella-base-en-v2 [Accessed 16-04--2024].

3. Taylor AI. [n. d.]. TaylorAI/bge-micro · Hugging Face - huggingface.co. https: //huggingface.co/TaylorAI/bge-micro [Accessed 16-04--2024].

4. The role of local dimensionality measures in benchmarking nearest neighbor search

5. Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, and Tong Wang. 2018. MS MARCO: A Human Generated MAchine Reading COmprehension Dataset. arXiv:1611.09268 [cs.CL]

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