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Register a new userFinQA: A Dataset of Numerical Reasoning over Financial Data
فنقة: مجموعة بيانات من التفكير العددي على البيانات المالية
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إن حجم البيانات المالية الهائلة يجعل من الصعب الوصول إلى البشر ويحللون قطاع الأعمال. تواجه المنطق العددي القوي بالمثل تحديات فريدة من نوعها في هذا المجال. في هذا العمل، نركز على الإجابة على الأسئلة العميقة على البيانات المالية، تهدف إلى أتمتة تحليل لجنة كبيرة من الوثائق المالية. على عكس المهام الحالية على المجال العام، يتضمن مجال التمويل التفكير العددي المعقد وفهم تمثيلات غير متجانسة. لتسهيل التقدم التحليلي، نقترح مجموعة بيانات جديدة واسعة النطاق، فنقة، مع أزواج الإجابة على السؤال حول التقارير المالية، التي كتبها خبراء ماليون. كما نبحث أيضا عن برامج المنطق الذهبي لضمان التوضيح الكامل. ونحن نقدم أيضا خطوط الأساس وإجراء تجارب شاملة في مجموعة البيانات الخاصة بنا. توضح النتائج أن النماذج الشعبية الكبيرة والمدربة مسبقا تنخفض بعيدا عن البشر الخبراء في الحصول على المعرفة المالية وفي التفكير العددي متعدد الخطوات المعقدة في هذه المعرفة. لدينا DataSet - أول نوع - يجب أن تتيح بحث مجتمعي كبير جديد في مجالات التطبيق المعقدة. تتوفر DataSet and Code علنا في HTTPS://github.com/czyssrs/finqa.
The sheer volume of financial statements makes it difficult for humans to access and analyze a business's financials. Robust numerical reasoning likewise faces unique challenges in this domain. In this work, we focus on answering deep questions over financial data, aiming to automate the analysis of a large corpus of financial documents. In contrast to existing tasks on general domain, the finance domain includes complex numerical reasoning and understanding of heterogeneous representations. To facilitate analytical progress, we propose a new large-scale dataset, FinQA, with Question-Answering pairs over Financial reports, written by financial experts. We also annotate the gold reasoning programs to ensure full explainability. We further introduce baselines and conduct comprehensive experiments in our dataset. The results demonstrate that popular, large, pre-trained models fall far short of expert humans in acquiring finance knowledge and in complex multi-step numerical reasoning on that knowledge. Our dataset -- the first of its kind -- should therefore enable significant, new community research into complex application domains. The dataset and code are publicly available at https://github.com/czyssrs/FinQA.
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