SLR-Bench / app.py
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import streamlit as st
import pandas as pd
# Title and description
st.set_page_config(page_title="SLR-BENCH Leaderboard", layout="wide")
st.title("SLR-BENCH Leaderboard")
st.markdown("""
This is a leaderboard displaying model performance metrics for the SLR-BENCH benchmark.
We report the models’ Logical Reasoning Level (LRL), syntax score,
stage-specific logical reasoning accuracy (basic, easy, medium, hard), total completion tokens, and inference cost.
Higher LRL and accuracy indicate superior logical reasoning; lower compute, greater efficiency. Performance drops
as complexity increases, while Reasoning LLMs consistently outperform conventional LLMs.
""")
# Load the CSV file
csv_file_path = "slr_bench_results.csv" # Update this path to your CSV file
try:
data = pd.read_csv(csv_file_path)
# Display the table
st.dataframe(data, use_container_width=True)
except FileNotFoundError:
st.error(f"CSV file not found at '{csv_file_path}'. Please ensure the file exists.")