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[Lihu Chen](https://chenlihu.com), [Gaël Varoquaux](https://gael-varoquaux.info/), [Fabian M. Suchanek](https://suchanek.name/).
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<br> Accepted by EACL Findings 2024
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PEARL-base is a
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for phrases and strings. <br>
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It offers powerful embeddings suitable for tasks like string matching, entity retrieval, entity clustering, and fuzzy join.
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🤗 [PEARL-small](https://huggingface.co/Lihuchen/pearl_small) 🤗 [PEARL-base](https://huggingface.co/Lihuchen/pearl_base)
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<br>
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[Lihu Chen](https://chenlihu.com), [Gaël Varoquaux](https://gael-varoquaux.info/), [Fabian M. Suchanek](https://suchanek.name/).
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<br> Accepted by EACL Findings 2024
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PEARL-base is a lightweight string embedding model. It is the tool of choice for semantic similarity computation for strings,
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creating excellent embeddings for string matching, entity retrieval, entity clustering, fuzzy join...
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It differs from typical sentence embedders because it incorporates phrase type information and morphological features,
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allowing it to better capture variations in strings.
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The model is a variant of [E5-base](https://huggingface.co/intfloat/e5-base-v2) finetuned on our constructed context-free [dataset](https://zenodo.org/records/10676475) to yield better representations
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for phrases and strings. <br>
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🤗 [PEARL-small](https://huggingface.co/Lihuchen/pearl_small) 🤗 [PEARL-base](https://huggingface.co/Lihuchen/pearl_base)
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<br>
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