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GreenLeaf Law Embed Tiny: A Compact Embedding Model for Legal Domain Retrieval
embeddinglegal retrievalfine-tuningknowledge distillation
2608.24936
Builder Relevance
3h ago80%
Abstract
A compact embedding model for legal domain retrieval that achieves competitive performance with limited parameters.
Reality Card
Core Claim
GreenLeaf-Tiny achieves 75.11% on the Massive Legal Embedding Benchmark (MLEB) while being a 0.6B parameter model.
Method / Result
Utilizes a two-stage training pipeline and a dataset of 3.4 million query-passage pairs.
Limitations
The model's performance may be limited by the quality and diversity of the training dataset.
Paper to code
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