Sentence-T5: text-to-text model extraction and contrastive sentence tuning

What is recorded here?

Compared first-token/mean encoder outputs and first decoder output as sentence representations, with projection/normalization and staged community-QA then labeled-NLI contrastive tuning.

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Scientific scope

Extraction choices and task metrics behave differently; encoder-only and encoder–decoder costs differ. Scaling results are empirical, not guaranteed for all sizes/tasks. Uses inherited T5 and contrastive training.

Read the original work

Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

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People and systems

Jianmo Ni; Gustavo Hernández Ábrego; Noah Constant; Ji Ma; Keith B. Hall; Daniel Cer; Yinfei Yang

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English catalogue narrative