Update FinAuditing dataset card: task categories, paper title, and GitHub link

README.md

@@ -1,4 +1,11 @@
 ---
+language:
+- en
+license: cc-by-4.0
+task_categories:
+- text-retrieval
+- text-classification
+- question-answering
 dataset_info:
   features:
   - name: query
@@ -20,28 +27,24 @@ configs:
   data_files:
   - split: test
     path: data/test-*
-task_categories:
-- text-generation
-license: cc-by-4.0
-language:
-- en
 papers:
-- title: "FinAuditing: Taxonomy-Grounded Financial Auditing Benchmark for Evaluating Large Language Models"
+- title: 'FinAuditing: A Financial Taxonomy-Structured Multi-Document Benchmark for
+    Evaluating LLMs'
   authors:
-    - Yan Wang
-    - Keyi Wang
-    - Shanshan Yang
-    - Jaisal Patel
-    - Jeff Zhao
-    - Fengran Mo
-    - Xueqing Peng
-    - Lingfei Qian
-    - Jimin Huang
-    - Guojun Xiong
-    - Xiao-Yang Liu
-    - Jian-Yun Nie
-  url: "https://arxiv.org/abs/2510.08886"
-  conference: "arXiv preprint, 2025"
+  - Yan Wang
+  - Keyi Wang
+  - Shanshan Yang
+  - Jaisal Patel
+  - Jeff Zhao
+  - Fengran Mo
+  - Xueqing Peng
+  - Lingfei Qian
+  - Jimin Huang
+  - Guojun Xiong
+  - Xiao-Yang Liu
+  - Jian-Yun Nie
+  url: https://arxiv.org/abs/2510.08886
+  conference: arXiv preprint, 2025
 tags:
 - finance
 - auditing
@@ -55,5 +58,24 @@ tags:
 # 🧾 FinAuditing Benchmark
 
 This dataset is introduced in the paper  
-**[FinAuditing: Taxonomy-Grounded Financial Auditing Benchmark for Evaluating Large Language Models](https://arxiv.org/abs/2510.08886)**  
-by Yan Wang, Keyi Wang, Shanshan Yang, Jaisal Patel, Jeff Zhao, Fengran Mo, Xueqing Peng, Lingfei Qian, Jimin Huang, Guojun Xiong, Xiao-Yang Liu, and Jian-Yun Nie (2025).
+**[FinAuditing: A Financial Taxonomy-Structured Multi-Document Benchmark for Evaluating LLMs](https://arxiv.org/abs/2510.08886)**  
+by Yan Wang, Keyi Wang, Shanshan Yang, Jaisal Patel, Jeff Zhao, Fengran Mo, Xueqing Peng, Lingfei Qian, Jimin Huang, Guojun Xiong, Xiao-Yang Liu, and Jian-Yun Nie (2025).
+
+The FinAuditing benchmark is designed to evaluate Large Language Models (LLMs) on financial auditing tasks, particularly their ability to reason over structured, interdependent, and taxonomy-driven financial documents. It addresses the challenges posed by the complexity of Generally Accepted Accounting Principles (GAAP) and the hierarchical structure of eXtensible Business Reporting Language (XBRL) filings. The benchmark defines three complementary subtasks: FinSM for semantic consistency, FinRE for relational consistency, and FinMR for numerical consistency, each targeting a distinct aspect of structured auditing reasoning.
+
+Code: https://github.com/The-FinAI/FinAuditing.git
+
+## 🌟 Overview
+
+The FinAuditing benchmark dataset is built from real US-GAAP-compliant XBRL filings and provides evaluation sets for various subtasks. For the evaluation framework, please refer to the [FinBen repository](https://github.com/The-FinAI/FinBen).
+
+### 📚 Datasets Released
+
+The following evaluation datasets are part of the FinAuditing benchmark:
+
+*   [**FinSM**](https://huggingface.co/datasets/TheFinAI/FinSM) - Evaluation set for the FinSM subtask within FinAuditing benchmark. This task follows an information retrieval paradigm: given a query describing a financial term (representing either currency or concentration of credit risk), an XBRL filing, and a US-GAAP taxonomy, the output is the set of mismatched US-GAAP tags after retrieval.
+*   [**FinRE**](https://huggingface.co/datasets/TheFinAI/FinRE) - Evaluation set for the FinRE subtask within FinAuditing benchmark. This is a relation extraction task: given two specific elements $e_1$ and $e_2$, an XBRL filing, and a US-GAAP taxonomy, the goal is to classify three relation error types.
+*   [**FinMR**](https://huggingface.co/datasets/TheFinAI/FinMR) - Evaluation set for the FinMR subtask within FinAuditing benchmark. This is a mathematical reasoning task: given two questions $q_1$ and $q_2$ (where $q_1$ concerns the extraction of a reported value and $q_2$ pertains to the calculation of the corresponding real value), an XBRL filing, and a US-GAAP taxonomy, the task is to extract the reported value for a given instance in the XBRL filing and to compute the numeric value for that instance, which is then used to verify whether the reported value is correct.
+*   [**FinSM\_Sub**](https://huggingface.co/datasets/TheFinAI/FinSM_Sub) - FinSM subset for ICAIF 2025.
+*   [**FinRE\_Sub**](https://huggingface.co/datasets/TheFinAI/FinRE_Sub) - FinRE subset for ICAIF 2025.
+*   [**FinMR\_Sub**](https://huggingface.co/datasets/TheFinAI/FinMR_Sub) - FinMR subset for ICAIF 2025.