GitHub / jingtaozhan / RepCONC

WSDM'22 Best Paper: Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jingtaozhan%2FRepCONC
PURL: pkg:github/jingtaozhan/RepCONC

Stars: 114
Forks: 11
Open issues: 2

License: mit
Language: Python
Size: 479 KB
Dependencies parsed at: Pending

Created at: almost 4 years ago
Updated at: almost 2 years ago
Pushed at: about 3 years ago
Last synced at: almost 2 years ago

Topics: dense-retrieval, efficiency, information-retrieval, neural-ranking, product-quantization

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