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README.md

@@ -47,8 +47,8 @@ Lemonade
 **Answers** : A list of possible answers to the question. This can be a multiple-choice set or open-ended responses. </br>
 **Correct Answer** : The answer that is deemed correct from the list of provided answers. </br>
 **Clip** : A reference to the video clip related to the question. </br>
-**Start** : The timestamp (in frame) in the clip where the question context begins. </br>
-**End** : The timestamp (in frame) in the clip where the question context ends. </br>
+**Start** : The timestamp (in frames) in the clip where the question context begins. </br>
+**End** : The timestamp (in frames) in the clip where the question context ends. </br>
 **Category** : The broad topic under which the question falls (Behavior understanding, Long-term understanding or Motion and Biomechanics) </br>
 **Subcategory** : A more refined classification within the category (Perception, Reasoning, Summarization, Session properties, Physical attributes, Kinematics) </br>
 **Difficulty** : The complexity level of the question (e.g., Easy, Medium, Hard)
@@ -66,7 +66,14 @@ The evaluation of the benchmark can be done through the following github reposit
 
 
 ## 🌟 Citations
-cite arxiv paper
+```
+@article{bonnetto2025epflsmartkitchen,
+  title={EPFL-Smart-Kitchen-30: Densely annotated cooking dataset with 3D kinematics to challenge video and language models},
+  author = {Andy Bonnetto and Haozhe Qi and Franklin Leong and Matea Tashkovska and Mahdi Rad and Solaiman Shokur and Friedhelm Hummel and Silvestro Micera and Marc Pollefeys and Alexander Mathis}
+  journal={},
+  year={2025}
+}
+```
 
 ## ❤️ Acknowledgments
 We thank Andy Bonnetto for the design of the dataset and  Matea Tashkovska for the adaptation of the evaluation platform. </br>