What is recorded here?
Replaced globally normalized softmax image-text contrastive loss with pairwise sigmoid classification, decoupling the objective from global batch normalization and enabling efficient distributed scaling.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Paired image-text pretraining and sigmoid classification are inherited. No-global-normalizer does not remove negative-pair computation, communication or all batch effects. Original v1 excludes later recipe gains.
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People and systems
Xiaohua Zhai; Basil Mustafa; Alexander Kolesnikov; Lucas Beyer
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
Zhai et al.: pairwise sigmoid language-image pretraining loss
Replaced globally normalized softmax image-text contrastive loss with pairwise sigmoid classification, decoupling the objective from global batch normalization and enabling efficient distributed scaling.
Scientific scope
Paired image-text pretraining and sigmoid classification are inherited. No-global-normalizer does not remove negative-pair computation, communication or all batch effects. Original v1 excludes later recipe gains.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Xiaohua Zhai; Basil Mustafa; Alexander Kolesnikov; Lucas Beyer
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.