Update README.md

README.md

@@ -119,7 +119,7 @@ The project code is available at https://github.com/famma-bench/bench-script.
 ## NEWS
 
 🔥 **Latest Updates**:
-- [2025/04] Release of an interactive notebook for exploring and analyzing the FAMMA dataset. [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://github.com/famma-bench/bench-script/blob/main/notebooks/FAMMA_1_dataset_inspection.ipynb)
+- [2025/04] Release of an interactive notebook for exploring and analyzing the FAMMA dataset. See [notebook examples](https://github.com/famma-bench/bench-script/tree/main/notebooks)
 - [2025/04]  Release of `release_livepro_txt`, a purely textual dataset that utilizes OCR to extract multimodal information and convert it into textual context for each question in `release_livepro`.
 - [2025/03]  Release of `release_basic_txt`, a purely textual dataset that utilizes OCR to extract multimodal information and convert it into textual context for each question in `release_basic`.
 - [2025/03]  Add `is_arithmetic` column in the dataset to indicate whether the question involves heavy compuation. 
@@ -209,7 +209,7 @@ If you use FAMMA in your research, please cite our paper as follows:
 ```latex
 @article{xue2024famma,
   title={FAMMA: A Benchmark for Financial Domain Multilingual Multimodal Question Answering},
-  author={Siqiao Xue, Tingting Chen, Fan Zhou, Qingyang Dai, Zhixuan Chu, and Hongyuan Mei},
+  author={Siqiao Xue, Xiaojing Li, Fan Zhou, Qingyang Dai, Zhixuan Chu, and Hongyuan Mei},
   journal={arXiv preprint arXiv:2410.04526},
   year={2024},
   url={https://arxiv.org/abs/2410.04526}