Change layout

app.py

@@ -77,13 +77,12 @@ def create_app():
             datatype="markdown",
             label="Leaderboard",
             elem_id="leaderboard-table",
+            show_search="search",
         )
 
         status_text = gr.Markdown()
-        refresh_button = gr.Button("Refresh leaderboard", variant="primary")
 
         demo.load(refresh_leaderboard, outputs=[leaderboard_table, status_text])
-        refresh_button.click(refresh_leaderboard, outputs=[leaderboard_table, status_text])
 
     return demo
 

src/about.py

@@ -1,12 +1,5 @@
-# Your leaderboard name
 TITLE = """<h1 align="center" id="space-title">Upgini MLE-Bench Tabular Leaderboard</h1>"""
 
-# What does your leaderboard evaluate?
 INTRODUCTION_TEXT = """
-This app mirrors the remote leaderboard so you always see the latest public results.
-Click **Refresh leaderboard** any time to re-download the CSV from GitHub.
-"""
-
-CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
-CITATION_BUTTON_TEXT = r"""
+This leaderboard mirrors the latest changes to [Upgini's MLE-Bench](https://github.com/upgini/mle-bench) leaderboard. It is a version of [MLE-bench](https://github.com/openai/mle-bench) that compares agent performance on tabular data. It uses exactly the same setup and differs just in the leaderboard view. We focus on tabular tasks and use [normalized score](https://github.com/upgini/mle-bench/?tab=readme-ov-file#mean-normalized-score) instead of medal percentage to compare differently scaled scores. The leaderboard is recomputed upon updating submitted runs from OpenAI repo.
 """