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Arxiv
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Domaino1s: Guiding LLM Reasoning for Explainable Answers in High-Stakes Domains
- Large Language Models (LLMs) for high-stakes domains like finance and legal QA often provide brief answers without explanations, reducing user confidence.
- Domaino1s introduces a method to enhance LLMs' reasoning abilities in high-stakes domains through supervised fine-tuning and tree search.
- Domaino1s utilizes CoT-stock-2k and CoT-legal-2k datasets for fine-tuning, activating domain-specific reasoning steps.
- Selective Tree Exploration and PROOF-Score metrics are proposed to improve model performance and explainability in stock investment and legal reasoning tasks.
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