Update README.md

README.md

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 `FAMMA` is a multi-modal financial Q&A benchmark dataset. The questions encompass three heterogeneous image types - tables, charts and text & math screenshots - and span eight subfields in finance, comprehensively covering topics across major asset classes. Additionally, all the questions are categorized by three difficulty levels — easy, medium, and hard - and are available in three languages — English, Chinese, and French. Furthermore, the questions are divided into two types: multiple-choice and open questions.
 
+More importantly, `FAMMA` provides a "live" benchmark for evaluating financial analysis capabilities of LLMs. The benchmark continuously collects new questions from real-world financial professionals, ensuring up-to-date and contamination-free evaluation. 
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 The leaderboard is regularly updated and can be accessed at https://famma-bench.github.io/famma/.  
 
 The project code is available at https://github.com/famma-bench/bench-script.
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 ## NEWS
 
 🔥 **Latest Updates**:
+- [2025/02]  Release of `release_v2501` dataset.
 - [2025/01]  Release of `release_v2406` dataset, now including answers and explanations with enhanced quality.
 - [2024/06]  Initial public release of `FAMMA` benchmark (based on the `release_v2406` dataset), along with our paper: [FAMMA: A Benchmark for Financial Domain Multilingual Multimodal Question Answering](https://arxiv.org/abs/2410.04526).