update logo

README.md

@@ -24,7 +24,8 @@ dataset_info:
   size_categories:
     - 10B<n<100B
 ---
-# <img align="left" width="50" height="50" src="imgs/openwebmath_logo.png" style="margin-top: -12px; margin-bottom: 0px;"> OpenWebMath
+<!-- # <img align="left" width="50" height="50" src="imgs/openwebmath_logo.png" style="margin-top: -12px; margin-bottom: 0px;"> OpenWebMath -->
+<img src="imgs/OpenWebMath-left.png">
 
 [Keiran Paster](https://keirp.com)\*, [Marco Dos Santos](#)\*, [Zhangir Azerbayev](https://zhangir-azerbayev.github.io/), [Jimmy Ba](https://jimmylba.github.io/)
 
@@ -84,12 +85,10 @@ OpenWebMath builds on the massive [Common Crawl](https://commoncrawl.org/) datas
 
 The OpenWebMath pipeline consists of five steps:
 1. **Prefiltering HTML Documents**:
-    - Apply a prefilter to all HTML documents in Common Crawl.
-    - Quickly judge whether documents have mathematical content.
-    - Skip documents without mathematical content to avoid extensive processing.
+    - We apply a simple prefilter to all HTML documents in Common Crawl in order to skip documents without mathematical content to unnecessary processing time.
     
 2. **Text Extraction**:
-    - Extract text, including LaTeX content, from the HTML documents.
+    - Extract text, including LaTeX content, from the HTML documents while removing boilerplate.
     
 3. **Content Classification and Filtering**:
     - Apply a [FastText language identification model](https://fasttext.cc/docs/en/language-identification.html) to keep only English documents.