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XuanYuan 2.0: A Large Chinese Financial Chat Model with Hundreds of Billions Parameters

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arxiv 2305.12002 v1 pith:ZLDPNLSZ submitted 2023-05-19 cs.CL

classification cs.CL
keywords chinesechatmodelsxuanyuanbillionsfinancialhundredslanguage
verification ladder T0 review T1 audit T2 compute T3 formal
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In recent years, pre-trained language models have undergone rapid development with the emergence of large-scale models. However, there is a lack of open-sourced chat models specifically designed for the Chinese language, especially in the field of Chinese finance, at the scale of hundreds of billions. To address this gap, we introduce XuanYuan 2.0, the largest Chinese chat model to date, built upon the BLOOM-176B architecture. Additionally, we propose a novel training method called hybrid-tuning to mitigate catastrophic forgetting. By combining general-domain with domain-specific knowledge and integrating the stages of pre-training and fine-tuning, XuanYuan 2.0 is capable of providing accurate and contextually appropriate responses in the Chinese financial domain.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. FinTeam: A Multi-Agent Collaborative Intelligence System for Comprehensive Financial Scenarios

    cs.CE 2025-07 conditional novelty 5.0 of 10

    A four-agent LLM pipeline trained with role-specific data improves human preference on comprehensive Chinese financial analysis tasks.

  2. Enterprise Large Language Model Evaluation Benchmark

    cs.AI 2025-06 reject novelty 5.0 of 10

    A 14-task enterprise LLM benchmark built mostly from GPT-4o-generated labels and scored by GPT-4o-as-judge shows open-source models closing the reasoning gap, but the dataset is not public and the evaluation is partly...

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