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English(EN) IHUBERT: Vector-Based Semantic Deduplication and Domain-Balanced Pretraining for Persian Resources

新的IHUBERT模型通过精选预训练提升波斯语理解能力

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了IHUBERT，一个基于RoBERTa-base编码器的新波斯语语言模型。该模型在Sepahr-Danesh集合中一个45 GB的精选数据集上进行了训练，总计约70-80亿个token。IHUBERT采用多阶段预处理流程，包括语义去重，以提高语料库质量并平衡领域表示。该模型在各种自然语言理解基准测试中表现强劲，尤其在抽取式问答任务中表现出色。 AI

影响 推进了波斯语语言建模能力，并为波斯语的NLU任务设定了新的基准。

排序理由 该集群描述了一篇详细介绍语言模型创建和评估的新研究论文。

在 arXiv cs.AI 阅读 →

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新的IHUBERT模型通过精选预训练提升波斯语理解能力

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该集群描述了一篇详细介绍语言模型创建和评估的新研究论文。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Arash Ghafouri, Mahdi Firouzmandi, Hossein Saberi, Mohammad Reza Hasani Ahangar ·

    IHUBERT：基于向量的语义去重和领域平衡预训练用于波斯语资源

    arXiv:2606.20089v1 Announce Type: cross Abstract: Persian pretrained language models (PLMs) are still limited by the scarcity of large-scale, high-quality pretraining corpora and by insufficient evaluation beyond standard classification and NER tasks. We present IHUBERT, a monoli…

  2. arXiv cs.AI TIER_1 English(EN) · Mohammad Reza Hasani Ahangar ·

    IHUBERT：基于向量的语义去重和领域平衡预训练用于波斯语资源

    Persian pretrained language models (PLMs) are still limited by the scarcity of large-scale, high-quality pretraining corpora and by insufficient evaluation beyond standard classification and NER tasks. We present IHUBERT, a monolingual Persian PLM trained from scratch with the Ro…

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