Papers with training infrastructure requirements

1 papers
LEAF: Knowledge Distillation of Text Embedding Models with Teacher-Aligned Representations (2026.acl-long)

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Challenge: a new framework for text embedding models is available for free . asymmetrical architectures allow for flexible asymmetry, while asynchronous architectures require small batches .
Approach: They propose a knowledge distillation framework for text embedding models that is compatible with their teacher . they publish leaf-ir, a 23M parameters information retrieval oriented model that ranks no.1 on BEIR .
Outcome: The proposed model is compatible with teacher, enabling flexible asymmetric architectures . it sets a new state-of-the-art (SOTA) on BEIR, and achieves no.1 on the leaderboard .

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