Update task category, add tags, and include survey paper link for InfiMM-WebMath-40B (#4)

- Update task category, add tags, and include survey paper link for InfiMM-WebMath-40B (2e66d95e186d5762ad0f417ea9965b23939e6af7)


Co-authored-by: Niels Rogge <[email protected]>

README.md

@@ -1,21 +1,26 @@
 ---
-license: odc-by
-task_categories:
-- text-generation
 language:
 - en
 - zh
+license: odc-by
+size_categories:
+- 10B<n<100B
+task_categories:
+- image-text-to-text
 tags:
 - pretrain
 - multi-modal
-size_categories:
-- 10B<n<100B
+- mathematical-reasoning
+- geometry
 ---
 
 # InfiMM-WebMath-40B Dataset
 
 [ArXiv](https://arxiv.org/abs/2409.12568)| [PDF](https://arxiv.org/pdf/2409.12568)
 
+This dataset is also discussed in the survey paper [A Survey of Deep Learning for Geometry Problem Solving](https://huggingface.co/papers/2507.11936).
+The accompanying reading list/code for the survey can be found at: https://github.com/majianz/gps-survey
+
 **InfiMM-WebMath-40B** is a large-scale, open-source multimodal dataset specifically designed for mathematical reasoning tasks. It incorporates both text and images, extracted from web documents, to advance the pre-training of Multimodal Large Language Models (MLLMs). The dataset is tailored to support sophisticated reasoning tasks that involve understanding both text and visual elements like diagrams, figures, and geometric plots.
 
 ## Dataset Overview
@@ -41,7 +46,7 @@ The dataset is organized in a format that captures both text and images in their
   "metadata": {           # Metadata containing information about the extraction process (e.g., processing details, timestamps).
     "ft_lang_label",      # Type of languages detected by fastText
     "ft_lang_prob",       # Probability of type of language detected by fastText
-    "math_prob",          # First round math content detection with high recal fastText model
+    "math_prob",          # First round math content detection with high recal FastText model
     "size",
     "snap",               # Timestamp of Common Crawl snapshot
     "text_gpt3_token_len",
@@ -51,12 +56,11 @@ The dataset is organized in a format that captures both text and images in their
     "punctuation_ratio",  
     "nsfw_num_words",     # Number of words which are NSFW
     "has_unicode_error",  # If there's any unicode error exists
-    "math_prob_llama3",   # Probability of second round math detection with high precision fastText model
+    "math_prob_llama3",   # Probability of second round math detection with high precision FastText model
   }
 }
 ```
 
-
 ### Interleaved Text and Images
 
 The **text_list** and **image_list** are designed as parallel arrays, maintaining the sequence of the document. This interleaving structure allows models to reconstruct the flow of the original document: