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  # Dialog2Flow joint target (BERT-base)
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- This is the original **D2F$_{joint}$** model introduced in the paper ["Dialog2Flow: Pre-training Soft-Contrastive Action-Driven Sentence Embeddings for Automatic Dialog Flow Extraction"](https://publications.idiap.ch/attachments/papers/2024/Burdisso_EMNLP2024_2024.pdf) published in the EMNLP 2024 main conference.
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  Implementation-wise, this is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or search.
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  # Dialog2Flow joint target (BERT-base)
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+ This is the original **D2F$_{joint}$** model introduced in the paper ["Dialog2Flow: Pre-training Soft-Contrastive Action-Driven Sentence Embeddings for Automatic Dialog Flow Extraction"](https://arxiv.org/abs/2410.18481) published in the EMNLP 2024 main conference.
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  Implementation-wise, this is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or search.
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