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README.md

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+---
+license: apache-2.0
+task_categories:
+- question-answering
+language:
+- zh
+- en
+pretty_name: e
+configs:
+  - config_name: cn
+    data_files:
+      - split: anomaly_information_tracing
+        path: cn/anomaly_information_tracing_cn.jsonl
+      - split: conterfactual
+        path: cn/conterfactual_cn.jsonl
+      - split: event_logic_reasoning
+        path: cn/event_logic_reasoning_cn.jsonl
+      - split: financial_data_description
+        path: cn/financial_data_description_cn.jsonl
+      - split: financial_multi_turn_perception
+        path: cn/financial_multi-turn_perception_cn.jsonl
+      - split: financial_quantitative_computation
+        path: cn/financial_quantitative_computation_cn.jsonl
+      - split: financial_report_analysis
+        path: cn/financial_report_analysis.jsonl
+      - split: stock_price_predict
+        path: cn/stock_price_predict_cn.jsonl
+      - split: user_sentiment_analysis
+        path: cn/user_sentiment_analysis_cn.jsonl
+  - config_name: en
+    data_files:
+      - split: anomaly_information_tracing
+        path: en/anomaly_information_tracing_en.jsonl
+      - split: conterfactual
+        path: en/conterfactual_en.jsonl
+      - split: event_logic_reasoning
+        path: en/event_logic_reasoning_en.jsonl
+      - split: financial_data_description
+        path: en/financial_data_description_en.jsonl
+      - split: financial_multi_turn_perception
+        path: en/financial_multi-turn_perception_en.jsonl
+      - split: financial_quantitative_computation
+        path: en/financial_quantitative_computation_en.jsonl
+      - split: stock_price_predict
+        path: en/stock_price_predict_en.jsonl
+      - split: user_sentiment_analysis
+        path: en/user_sentiment_analysis_en.jsonl
+---
+
+<p align="center">
+  <h1 align="center">BizFinBench.v2: A Unified Dual-Mode Bilingual Benchmark for Expert-Level Financial Capability Alignment</h1>
+    <p align="center">
+    <span class="author-block">
+      Xin Guo<sup>1,2,*</sup> </a>,</span>
+                <span class="author-block">
+      Rongjunchen Zhang<sup>1,*,♠</sup></a>, Guilong Lu<sup>1</sup>, Xuntao Guo<sup>1</sup>, Jia Shuai<sup>1</sup>, Zhi Yang<sup>2</sup>, Liwen Zhang<sup>2,♠</sup>
+    </span>
+    </div>
+    <div class="is-size-5 publication-authors" style="margin-top: 10px;">
+        <span class="author-block">
+            <sup>1</sup>HiThink Research, <sup>2</sup>Shanghai University of Finance and Economics
+        </span>
+        <br>
+        <span class="author-block">
+            <sup>*</sup>Co-first authors, <sup>♠</sup>Corresponding author, zhangrongjunchen@myhexin.com,zhang.liwen@shufe.edu.cn
+        </span>
+    </div>
+  </p>
+  <p>
+  📖<a href="https://arxiv.org/abs/2601.06401">Paper</a> |🏠<a href="https://hithink-research.github.io/BizFinBench.v2/">Homepage</a>
+  </p>
+<div align="center"></div>
+<p align="center">
+
+**BizFinBench.v2** is the secend release of [BizFinBench](https://github.com/HiThink-Research/BizFinBench). It is built entirely on real-world user queries from Chinese and U.S. equity markets. It bridges the gap between academic evaluation and actual financial operations.
+
+<img src="static/score_sequence.png" alt="Evaluation Result">
+
+### 🌟 Key Features
+
+* **Authentic & Real-Time:** 100% derived from real financial platform queries, integrating online assessment capabilities.
+* **Expert-Level Difficulty:** A challenging dataset of **29,578 Q&A pairs** requiring professional financial reasoning.
+* **Comprehensive Coverage:** Spans **4 core business scenarios**, 8 fundamental tasks, and 2 online tasks.
+
+### 📊 Key Findings
+* **High Difficulty:** Even **ChatGPT-5** achieves only 61.5% accuracy on main tasks, highlighting a significant gap vs. human experts.
+* **Online Prowess:** **DeepSeek-R1** outperforms all other commercial LLMs in dynamic online tasks, achieving a total return of 13.46% with a maximum drawdown of -8%.
+
+## 📢 News 
+- 🚀 [06/01/2026] TBD
+
+## 📕 Data Distrubution
+BizFinBench.v2 contains multiple subtasks, each focusing on a different financial understanding and reasoning ability, as follows:
+
+### Distribution Visualization
+<div align="center">
+    <img src="static/distribution.png" alt="Data Distribution" width="600">
+</div>
+
+### Detailed Statistics
+| Scenarios | Tasks | Avg. Input Tokens | # Questions |
+|:---|:---|---:|---:|
+| **Business Information Provenance** | Anomaly Information Tracing | 8,679 | 4,000 |
+| | Financial Multi-turn Perception | 10,361 | 3,741 |
+| | Financial Data Description | 3,577 | 3,837 |
+| **Financial Logic Reasoning** | Financial Quantitative Computation | 1,984 | 2,000 |
+| | Event Logic Reasoning | 437 | 4,000 |
+| | Counterfactual Inference | 2,267 | 2,000 |
+| **Stakeholder Feature Perception** | User Sentiment Analysis | 3,326 | 4,000 |
+| | Financial Report Analysis | 19,681 | 2,000 |
+| **Real-time Market Discernment** | Stock Price Prediction | 5,510 | 4,000 |
+| | Portfolio Asset Allocation | — | — |
+| **Total** | **—** | **—** | **29,578** |
+
+
+## ✒️Citation
+
+```
+Coming Soon
+```
+
+## 📄 License
+![Code License](https://img.shields.io/badge/Code%20License-Apache_2.0-green.svg) ![Data License](https://img.shields.io/badge/Data%20License-CC%20By%20NC%204.0-red.svg) **Usage and License Notices**: The data and code are intended and licensed for research use only.
+License: Attribution-NonCommercial 4.0 International It should abide by the policy of OpenAI: https://openai.com/policies/terms-of-use
+
+## 💖 Acknowledgement
+* Special thanks to Ning Zhang, Siqi Wei, Kai Xiong, Kun Chen and colleagues at HiThink Research's data team for their support in building BizFinBench.v2.
+

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