Update README.md

README.md

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 ## Model Description
 
-CrystalChat-7B based multi-modal large language model (MLLM) mimics the training recipe used for Vicuna-7B based [LLaVa-v1.5](https://huggingface.co/docs/transformers/main/model_doc/llava). CrystalChat-7B based MLLMs models are entirely transparent, having open-sourced all materials, including code, data, model checkpoint, intermediate results, and more at [TODO: Add paper link](). CrystalChat-7B-Web2Code MLLM is specialized in webpage images-to-html code generation.
-
+CrystalChat-7B based multi-modal large language model (MLLM) mimics the training recipe used for Vicuna-7B based [LLaVa-v1.5](https://huggingface.co/docs/transformers/main/model_doc/llava). CrystalChat-7B based MLLMs models are entirely transparent, having open-sourced all materials, including code, data, model checkpoint, intermediate results, and more at [Web2Code: A Large-scale Webpage-to-Code Dataset
+and Evaluation Framework for Multimodal LLMs](https://arxiv.org/pdf/2406.20098). CrystalChat-7B-Web2Code MLLM is specialized in webpage images-to-html code generation.
+
+## Web2Code Dataset
+Our Web2Code instruction tuning dataset construction and instruction generation process
+involves four key components: 
+1.  Creation of new webpage image-code pair data: We generated
+high-quality HTML webpage-code pairs following the CodeAlpaca prompt [6] using GPT-3.5 and
+convert them into instruction-following data. (2) Refinement of existing webpage code generation
+data: We transform existing datasets including WebSight [ 22 ] and Pix2Code [ 4] into an instruction-
+following data format similar to LLaVA data [33 ], so they can be used as instruction-following data
+to train MLLMs. (3) Creation of a new text question-answer pair data: We generated a new question-
+answer pair dataset utilizing our new GPT-3.5 generated data from (1) for webpage understanding.
+(4) Refinement of existing webpage understanding data: We refine the WebSRC [ 10] question-answer
+data to improve its quality using the GPT-4. 
 
 ## Evaluations