update instruction

app.py

@@ -194,17 +194,21 @@ Below we describe how to use the tool. Also feel free to check out the [video]()
 
 ##### Input
 - The tool requires two inputs: (1) an academic paper's abstract in a text format, (2) and a potential reviewer's [Semantic Scholar](https://www.semanticscholar.org/) profile link. Once you put in a valid profile link, the reviewer's name will be displayed. 
-- Once the name is confirmed, press the `What Makes this a Good Match?` button.
-##### Similar Papers From the Reviewer
-- Based on the input information above, the tool will first search for similar papers from the reviewer's previous publications using [Semantic Scholar API](https://www.semanticscholar.org/product/api). 
-- It will list top 10 similar papers along with the **affinity scores** (ranging from 0 -1) for each, computed using text representations from a [language model](https://github.com/allenai/specter/tree/master/specter).
-- You can click on different papers to see title, abstract, and affinity scores in detail. 
-##### Relevant Parts
-- Below the list of papers, we highlight relevant parts in the selected paper compared to the submission abstract.
-- On the left, you will see individual sentences from the submission abstract you can select from.
-- On the right, you will see the abstract of the selected paper, with **highlights**.
-- **<span style="color:black;background-color:#DB7262;">Red highlights</span>**: sentences from the reviewer's paper abstract with high semantic similarity to the selected sentence.
-- **<span style="color:black;background-color:#5296D5;">Blue highlights</span>**: phrases from the reviewer's paper abstract that is included in the selected sentence.
+- Once the name is confirmed, press the `What Makes This a Good Match?` button.
+- Based on the input information, the tool will first search for similar papers from the reviewer's previous publications using [Semantic Scholar API](https://www.semanticscholar.org/product/api). 
+##### Relevant Parts from Top Papers
+- You will be shown three most relevant papers from the reviewer with high **affinity scores** (ranging from 0 - 1) computed using text representations from a [language model](https://github.com/allenai/specter/tree/master/specter). 
+- For each of the paper, we present relevant pieces of information from the submission and the paper: two pairs of (sentence relevance score, sentence from the submission abstract, sentnece from the paper abstract)
+- **<span style="color:black;background-color:#5296D5;">Blue highlights</span>** inidicate phrases that are included in both sentences.
+##### More Relevant Parts
+- If the information above is not enough, click `See more relevant parts from other papers` button. 
+- You will see a list top 10 similar papers along with the affinity scores for each.
+- You can select different papers from the list to see title, abstract, and affinity scores in detail. 
+- Below the list of papers, we highlight relevant parts from the selected paper to different sentences of the submission abstract.
+- On the left, you will see individual sentences from the submission abstract to select from.
+- On the right, you will see the abstract of the selected paper, with **highlights** incidating relevant parts to the selected sentence.
+- **<span style="color:black;background-color:#DB7262;">Red highlights</span>**: sentences with high semantic similarity to the selected sentence.
+- **<span style="color:black;background-color:#5296D5;">Blue highlights</span>**: phrases included in the selected sentence.
 - To see relevant parts in a different paper from the reviewer, select the new paper.
 -------
         """
@@ -307,7 +311,7 @@ Below we describe how to use the tool. Also feel free to check out the [video]()
 
     ## Show more button
     with gr.Row():
-        see_more_rel_btn = gr.Button('See more relevant parts from papers', visible=False)
+        see_more_rel_btn = gr.Button('See more relevant parts from other papers', visible=False)
     
     ### PAPER INFORMATION