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README.md

@@ -1,56 +1,42 @@
----
-configs:
-  - config_name: benchmark
-    data_files:
-      - split: test
-        path: vision_language/FCMBench_v1.0_testset_full.jsonl
-license: apache-2.0
-task_categories:
-- table-question-answering
-- text-classification
-pretty_name: FCMBench
-size_categories:
-- 10K<n<100K
----
+![](assets/FCMBench_logo.jpg)
 
-![Main Image](https://github.com/QFIN-tech/FCMBench/raw/main/assets/FCMBench_logo.jpg)
 
 **FCMBench** is a multimodal benchmark for credit-risk–oriented workflows. It aims to provide a standard playground to promote collaborative development between academia and industry and provides standardized datasets, prompts, and evaluation scripts across multiple tracks (image, video, speech, agents, etc.)
 
 [简体中文](./README_cn.md)
 
 ## 🔥 News 
+- 【**2026. 03. 16**】✨ We released **FCMBench-V1.1**. This version adds English document images and corresponding QA pairs, expands the covered document types to 26, and increases the dataset to 5,198 images and 13,806 QA samples.
+- 【**2026. 01. 01**】We are proud to launch **FCMBench-V1.0**, which covers 18 core certificate types, including 4,043 privacy-compliant images and 8,446 QA samples. It involves 3 types of Perception tasks and 4 types of Reasoning tasks, which are cross-referenced with 10 categories of robustness inferences. All the tasks and inferences are derived from real-world critical scenarios.
 
-
-- 【**2026. 01. 01**】✨ We are proud to launch [**FCMBench-V1.0**](https://github.com/QFIN-tech/FCMBench/tree/main/vision_language), which covers 18 core certificate types, including 4,043 privacy-compliant images and 8,446 QA samples. It involves 3 types of Perception tasks and 4 types of Reasoning tasks, which are cross-referenced with 10 categories of robustness inferences. All the tasks and inferences are derived from real-world critical scenarios.
-
-> **Status:** Public release (v1.0).  
+> **Status:** Public release (v1.1).  
 > **Maintainers:** [奇富科技 / Qfin Holdings](https://github.com/QFIN-tech)  
-> **Contact:** [yangyehui-jk@qifu.com]
+> **Contact:** [yangyehuisw@126.com]
 
 ---
 
 ## Tracks Overview
 
-### 1) Vision-Language Track (✅ Available, **FCMBench-V1.0**)
+### 1) Vision-Language Track (✅ Available)
 
 Image-based financial document understanding: 
 
-- **Entry:** [Vision-Language Track](https://github.com/QFIN-tech/FCMBench/tree/main/vision_language)
+- **Entry:** [Vision-Language Track](vision_language)
 - **Inputs:** document images + text prompts (JSONL, one sample per line)
 - **Outputs:** text responses (JSONL, one sample per line)
-- **Evaluation:** [Evaluation Script](https://github.com/QFIN-tech/FCMBench/blob/main/vision_language/evaluation.py)
+- **Evaluation:** [Evaluation Script](vision_language/evaluation.py)
 
 #### Paper & Project Links
 - [**Paper (arXiv)**](https://arxiv.org/abs/2601.00150)
-- [**Paper (PDF)**](https://arxiv.org/pdf/2601.00150)
+- [**Paper (PDF)**](https://github.com/QFIN-tech/FCMBench/tree/main/TechnicalReport)
 - [**Project Page**](https://github.com/QFIN-tech/FCMBench/tree/main/vision_language)
-- [**Leaderboard**](vision_language/LEADERBOARD.md)
-- [**Dataset (ModelScope)**](https://modelscope.cn/datasets/QFIN/FCMBench-V1.0)
-- [**Dataset (Hugging Face)**](https://huggingface.co/datasets/QFIN/FCMBench-V1.0)
+- [**Leaderboard**](https://qfin-tech.github.io/FCMBench)
+- [**Sample Data**](https://qfin-tech.github.io/FCMBench/Examples.html)
+- [**Dataset (ModelScope)**](https://modelscope.cn/datasets/QFIN/FCMBench-Data)
+- [**Dataset (Hugging Face)**](https://huggingface.co/datasets/QFIN/FCMBench-Data)
 
 #### Reference Model Demo
-We also provide access to an interactive demo of our Qfin-VL-Instruct model, which achieves strong performance on FCMBench-V1.0.
+We also provide access to an interactive demo of our Qfin-VL-Instruct model, which achieves strong performance on FCMBench.
 If you are interested in trying the Gradio demo, please contact [yangyehui-jk@qifu.com] with the following information:
 - Name
 - Affiliation / Organization
@@ -76,4 +62,8 @@ Access will be granted on a case-by-case basis.
       primaryClass={cs.CV},
       url={https://arxiv.org/abs/2601.00150}, 
 }
-```
+```
+
+## Star History
+
+[![Star History Chart](https://api.star-history.com/svg?repos=QFIN-tech/FCMBench&type=date&legend=top-left)](https://www.star-history.com/#QFIN-tech/FCMBench&type=date&legend=top-left)

README_cn.md

@@ -1,34 +1,23 @@
----
-configs:
-  - config_name: benchmark
-    data_files:
-      - split: test
-        path: vision_language/FCMBench_v1.0_testset_full.jsonl
-license: apache-2.0
-task_categories:
-- table-question-answering
-- text-classification
-pretty_name: FCMBench
-size_categories:
-- 10K<n<100K
----
+![](assets/FCMBench_logo.jpg)
 
-![Main Image](https://github.com/QFIN-tech/FCMBench/raw/main/assets/FCMBench_logo.jpg)
-
-[English Version](./README.md)
 
 **FCMBench** 是一个面向信贷风控工作流的多模态基准测试（benchmark）。它旨在提供一个标准化的“试验场”，促进学术界与产业界的协同开发，并在多个赛道（图像、视频、语音、智能体等）上提供标准化的数据集、提示词（prompts）与评测脚本。
 
+[English Version](./README.md)
+
 ## 🔥 新闻
-- 【**2026. 01. 01**】✨ 我们很高兴发布 [**FCMBench-V1.0**](https://github.com/QFIN-tech/FCMBench/tree/main/vision_language)，该版本覆盖 18 类核心证件类型，包含 4,043 张符合隐私合规要求的图像与 8,446 条问答样本。其任务体系涵盖 3 类感知（Perception）任务与 4 类推理（Reasoning）任务，并与 10 类健壮性推理（robustness inferences）交叉引用。所有任务与推理过程均来源于真实世界的关键业务场景。
+- 【**2026. 03. 16**】✨ 我们发布了**FCMBench-V1.1**，该版本加入了英文证件图像和相关问答对，覆盖的证件类型增加至 26 个，图像增加至 5,198 张，问答样本增加至 13,806 条。
+- 【**2026. 01. 01**】我们很高兴发布**FCMBench-V1.0**，该版本覆盖 18 类核心证件类型，包含 4,043 张符合隐私合规要求的图像与 8,446 条问答样本。其任务体系涵盖 3 类感知（Perception）任务与 4 类推理（Reasoning）任务，并与 10 类健壮性推理（robustness inferences）交叉引用。所有任务与推理过程均来源于真实世界的关键业务场景。
 
-> **状态：** 公开发布（v1.0）。  
+> **状态：** 公开发布（v1.1）。  
 > **维护者：** [奇富科技 / Qfin Holdings](https://github.com/QFIN-tech)  
 > **联系方式：** [yangyehui-jk@qifu.com]
 
+---
+
 ## 赛道概览
 
-### 1) 视觉-语言赛道（✅ 已开放，**FCMBench-V1.0**）
+### 1) 视觉-语言赛道（✅ 已开放）
 
 基于图像的金融文档理解：
 
@@ -41,12 +30,12 @@ size_categories:
 - [**技术报告（arXiv）**](https://arxiv.org/abs/2601.00150)
 - [**技术报告（PDF）**](https://arxiv.org/pdf/2601.00150)
 - [**项目主页**](https://github.com/QFIN-tech/FCMBench/tree/main/vision_language)
-- [**排行榜**](vision_language/LEADERBOARD.md)
-- [**数据集（ModelScope）**](https://modelscope.cn/datasets/QFIN/FCMBench-V1.0)
-- [**数据集（Hugging Face）**](https://huggingface.co/datasets/QFIN/FCMBench-V1.0)
+- [**排行榜**](https://qfin-tech.github.io/FCMBench)
+- [**数据集（ModelScope）**](https://modelscope.cn/datasets/QFIN/FCMBench-Data)
+- [**数据集（Hugging Face）**](https://huggingface.co/datasets/QFIN/FCMBench-Data)
 
 #### 参考模型 Demo
-我们也提供 Qfin-VL-Instruct 模型的交互式演示（demo）访问，该模型在 FCMBench-V1.0 上表现强劲。  
+我们也提供 Qfin-VL-Instruct 模型的交互式演示（demo）访问，该模型在 FCMBench 上表现强劲。  
 如果你希望试用 Gradio demo，请将以下信息发送至 [yangyehui-jk@qifu.com]：
 - 姓名
 - 所属单位 / 组织
@@ -63,6 +52,7 @@ size_categories:
 
 ## 引用
 ```
+
 @misc{yang2026fcmbenchcomprehensivefinancialcredit,
       title={FCMBench: A Comprehensive Financial Credit Multimodal Benchmark for Real-world Applications}, 
       author={Yehui Yang and Dalu Yang and Wenshuo Zhou and Fangxin Shang and Yifan Liu and Jie Ren and Haojun Fei and Qing Yang and Yanwu Xu and Tao Chen},
@@ -72,4 +62,9 @@ size_categories:
       primaryClass={cs.CV},
       url={https://arxiv.org/abs/2601.00150}, 
 }
-```
+
+```
+
+## Star History
+
+[![Star History Chart](https://api.star-history.com/svg?repos=QFIN-tech/FCMBench&type=date&legend=top-left)](https://www.star-history.com/#QFIN-tech/FCMBench&type=date&legend=top-left)