Update src/display/about.py

src/display/about.py

@@ -48,13 +48,20 @@ currently consists of 15 individual tasks, leveraging pre-existing Czech dataset
 including ARC, GSM8K, MMLU, and TruthfulQA. This work is brought to you by CIIRC CTU and VSB Ostrava.
 
 Key Features and Benefits:
-- **Tailored for the Czech Language:** The benchmark includes both original Czech datasets and adapted versions of international datasets, ensuring relevant evaluation of model performance in the Czech context.
-- **Wide Range of Tasks:** It contains 15 different tasks that cover various aspects of language understanding and text generation, enabling a comprehensive assessment of the model's capabilities.
-- **Universal model support:** The universal text-to-text evaluation approach adopted in CzechBench allows for direct comparison of models with varying levels of internal access, including commercial APIs.
-- **Ease of Use:** The benchmark is designed to be easily integrated into your development process, saving time and resources during model testing and improvement.
-- **Up-to-date and Relevant:** We regularly update our datasets to reflect the latest findings and trends in language model development.
-By using CzechBench, you will gain deep insights into the strengths and weaknesses of your models, allowing you to better focus on key areas for optimization. 
-This will not only improve the performance of your models but also enhance their real-world deployment in various Czech contexts.
+- **Tailored for the Czech Language:** 
+CzechBench includes both original Czech datasets and adapted versions of international datasets, ensuring relevant evaluation of model performance in the Czech context.
+- **Wide Range of Tasks:** 
+It contains 15 different tasks that cover various aspects of language understanding and text generation, enabling a comprehensive assessment of the model's capabilities.
+- **Bilingual performance analysis:**
+CzechBench also offers a parallel collection of 9 English tasks corresponding to the Czech versions included in the main suite. 
+This allows for direct comparison of model performance across both languages with equivalent conditions in terms of prompt formulation and few-shot example selection.
+- **Universal model support:** 
+The universal text-to-text evaluation approach adopted in CzechBench allows for direct comparison of models with varying levels of internal access, including commercial APIs.
+- **Ease of Use:** 
+The benchmark is built upon a commonly used evaluation framework with wide support for state-of-the-art models and inference acceleration tools.
+- **Empowering decisions:**
+Whether you are a business looking for the best LLM solution to base your application on, or a research team trying to maximize the capabilities of the models they are developing,
+CzechBench will help you gain insights into particular strengths and weeknesses of individual models and better focus on key areas for optimization.
 
 Below, you can find the up-to-date loaderboard of models evaluated on CzechBench. 
 For more information on the included benchmarks and instructions on evaluating your own models, please visit the "About" section below.