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Avijit Ghosh commited on
Commit
981ea1d
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1 Parent(s): 3d19330

removed notebook

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Files changed (2) hide show
  1. .gitignore +2 -0
  2. temp.ipynb +0 -568
.gitignore CHANGED
@@ -1,2 +1,4 @@
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  temp/
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  .env
 
 
 
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  temp/
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  .env
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+ *.ipynb
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+ *.ipynb_checkpoints/
temp.ipynb DELETED
@@ -1,568 +0,0 @@
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- {
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- "cells": [
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- {
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- "cell_type": "code",
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- "execution_count": 20,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "import pandas as pd"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 21,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "df = pd.read_csv('DemoData.csv')"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 22,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "import pandas as pd\n",
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- "import yaml\n",
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- "import os\n",
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- "import ast\n",
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- "\n",
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- "# Create a folder to store YAML files if it doesn't exist\n",
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- "if not os.path.exists('configs'):\n",
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- " os.makedirs('configs')\n",
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- "\n",
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- "# Iterate over each row in the DataFrame\n",
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- "for index, row in df.iterrows():\n",
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- " # Extract Metaname and use it as the filename for YAML\n",
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- " filename = str(row['Metaname']) + '.yaml'\n",
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- " # Convert 'Screenshots' column to a Python list\n",
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- " screenshots_list = None\n",
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- " try:\n",
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- "\n",
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- " screenshots_list = ast.literal_eval(row['Screenshots'])\n",
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- " except:\n",
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- " screenshots_list = []\n",
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- " # Remove the 'Metaname' and 'Screenshots' columns from the data to be converted to YAML\n",
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- " row_data = row.drop(['Metaname', 'Screenshots'])\n",
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- " # Convert the remaining data to a dictionary\n",
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- " data_dict = row_data.to_dict()\n",
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- " # Add the 'Screenshots' list to the dictionary\n",
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- " data_dict['Screenshots'] = screenshots_list\n",
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- " # Write the data as YAML to a new file\n",
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- " with open(os.path.join('configs', filename), 'w') as yamlfile:\n",
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- " yaml.dump(data_dict, yamlfile, default_flow_style=False)"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 5,
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- "metadata": {},
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- "outputs": [
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- {
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- "data": {
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- "text/html": [
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- "<div>\n",
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- "<style scoped>\n",
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- " .dataframe tbody tr th:only-of-type {\n",
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- " vertical-align: middle;\n",
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- " }\n",
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- "\n",
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- " .dataframe tbody tr th {\n",
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- " vertical-align: top;\n",
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- " }\n",
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- "\n",
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- " .dataframe thead th {\n",
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- " text-align: right;\n",
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- " }\n",
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- "</style>\n",
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- "<table border=\"1\" class=\"dataframe\">\n",
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- " <thead>\n",
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- " <tr style=\"text-align: right;\">\n",
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- " <th></th>\n",
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- " <th>Group</th>\n",
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- " <th>Modality</th>\n",
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- " <th>Level</th>\n",
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- " <th>Metaname</th>\n",
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- " <th>Suggested Evaluation</th>\n",
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- " <th>What it is evaluating</th>\n",
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- " <th>Considerations</th>\n",
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- " <th>Link</th>\n",
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- " <th>URL</th>\n",
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- " <th>Screenshots</th>\n",
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- " <th>Applicable Models</th>\n",
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- " <th>Datasets</th>\n",
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- " <th>Hashtags</th>\n",
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- " </tr>\n",
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- " </thead>\n",
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- " <tbody>\n",
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- " <tr>\n",
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- " <th>0</th>\n",
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- " <td>BiasEvals</td>\n",
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- " <td>Model</td>\n",
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- " <td>weat</td>\n",
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- " <td>Word Embedding Association Test (WEAT)</td>\n",
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- " <td>Associations and word embeddings based on Impl...</td>\n",
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- " <td>Although based in human associations, general ...</td>\n",
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- " <td>Semantics derived automatically from language ...</td>\n",
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- " <td>https://researchportal.bath.ac.uk/en/publicati...</td>\n",
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- " <td>['Images/WEAT1.png', 'Images/WEAT2.png']</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " </tr>\n",
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- " <tr>\n",
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- " <th>1</th>\n",
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- " <td>BiasEvals</td>\n",
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- " <td>Text</td>\n",
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- " <td>Model</td>\n",
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- " <td>wefat</td>\n",
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- " <td>Word Embedding Factual As\\nsociation Test (WEFAT)</td>\n",
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- " <td>Associations and word embeddings based on Impl...</td>\n",
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- " <td>https://researchportal.bath.ac.uk/en/publicati...</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <tr>\n",
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- " <th>2</th>\n",
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- " <td>BiasEvals</td>\n",
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- " <td>Dataset</td>\n",
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- " <td>stereoset</td>\n",
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- " <td>StereoSet</td>\n",
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- " <td>Protected class stereotypes</td>\n",
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- " <td>Automating stereotype detection makes distingu...</td>\n",
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- " <td>StereoSet: Measuring stereotypical bias in pre...</td>\n",
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- " <td>https://arxiv.org/abs/2004.09456</td>\n",
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- " <td>NaN</td>\n",
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- " </tr>\n",
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- " <th>3</th>\n",
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- " <td>BiasEvals</td>\n",
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- " <td>Text</td>\n",
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- " <td>Dataset</td>\n",
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- " <td>crwospairs</td>\n",
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- " <td>Crow-S Pairs</td>\n",
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- " <td>Protected class stereotypes</td>\n",
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- " <td>Automating stereotype detection makes distingu...</td>\n",
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- " <td>CrowS-Pairs: A Challenge Dataset for Measuring...</td>\n",
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- " <td>https://arxiv.org/abs/2010.00133</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " </tr>\n",
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- " <tr>\n",
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- " <th>4</th>\n",
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- " <td>BiasEvals</td>\n",
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- " <td>Text</td>\n",
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- " <td>Output</td>\n",
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- " <td>honest</td>\n",
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- " <td>HONEST: Measuring Hurtful Sentence Completion ...</td>\n",
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- " <td>Protected class stereotypes and hurtful language</td>\n",
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- " <td>Automating stereotype detection makes distingu...</td>\n",
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- " <td>HONEST: Measuring Hurtful Sentence Completion ...</td>\n",
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- " <td>https://aclanthology.org/2021.naacl-main.191.pdf</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " </tr>\n",
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- " <tr>\n",
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- " <th>5</th>\n",
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- " <td>BiasEvals</td>\n",
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- " <td>Image</td>\n",
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- " <td>Model</td>\n",
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- " <td>ieat</td>\n",
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- " <td>Image Embedding Association Test (iEAT)</td>\n",
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- " <td>Embedding associations</td>\n",
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- " <td>Although based in human associations, general ...</td>\n",
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- " <td>Image Representations Learned With Unsupervise...</td>\n",
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- " <td>https://dl.acm.org/doi/abs/10.1145/3442188.344...</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " </tr>\n",
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- " <tr>\n",
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- " <th>6</th>\n",
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- " <td>BiasEvals</td>\n",
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- " <td>Image</td>\n",
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- " <td>Dataset</td>\n",
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- " <td>imagedataleak</td>\n",
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- " <td>Dataset leakage and model leakage</td>\n",
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- " <td>Gender and label bias</td>\n",
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- " <td>NaN</td>\n",
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- " <td>Balanced Datasets Are Not Enough: Estimating a...</td>\n",
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- " <td>https://arxiv.org/abs/1811.08489</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " </tr>\n",
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- " <tr>\n",
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- " <th>7</th>\n",
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- " <td>BiasEvals</td>\n",
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- " <td>Image</td>\n",
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- " <td>Output</td>\n",
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- " <td>stablebias</td>\n",
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- " <td>Characterizing the variation in generated images</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>Stable bias: Analyzing societal representation...</td>\n",
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- " <td>https://arxiv.org/abs/2303.11408</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " </tr>\n",
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- " <tr>\n",
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- " <th>8</th>\n",
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- " <td>BiasEvals</td>\n",
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- " <td>Image</td>\n",
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- " <td>Output</td>\n",
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- " <td>homoglyphbias</td>\n",
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- " <td>Effect of different scripts on text-to-image g...</td>\n",
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- " <td>It evaluates generated images for cultural ste...</td>\n",
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- " <td>NaN</td>\n",
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- " <td>Exploiting Cultural Biases via Homoglyphs in T...</td>\n",
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- " <td>https://arxiv.org/pdf/2209.08891.pdf</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " </tr>\n",
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- " <tr>\n",
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- " <th>9</th>\n",
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- " <td>BiasEvals</td>\n",
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- " <td>Audio</td>\n",
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- " <td>Taxonomy (?)</td>\n",
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- " <td>notmyvoice</td>\n",
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- " <td>Not My Voice! A Taxonomy of Ethical and Safety...</td>\n",
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- " <td>Lists harms of audio/speech generators</td>\n",
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- " <td>Not necessarily evaluation but a good source o...</td>\n",
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- " <td>Not My Voice! A Taxonomy of Ethical and Safety...</td>\n",
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- " <td>https://arxiv.org/pdf/2402.01708.pdf</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " </tr>\n",
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- " <tr>\n",
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- " <th>10</th>\n",
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- " <td>BiasEvals</td>\n",
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- " <td>Video</td>\n",
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- " <td>Output</td>\n",
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- " <td>videodiversemisinfo</td>\n",
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- " <td>Diverse Misinformation: Impacts of Human Biase...</td>\n",
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- " <td>Human led evaluations of deepfakes to understa...</td>\n",
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- " <td>Repr. harm, incite violence</td>\n",
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- " <td>Diverse Misinformation: Impacts of Human Biase...</td>\n",
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- " <td>https://arxiv.org/abs/2210.10026</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " </tr>\n",
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- " <tr>\n",
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- " <th>11</th>\n",
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- " <td>Privacy</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " <td>NaN</td>\n",
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- " </tr>\n",
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- " </tbody>\n",
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- "</table>\n",
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- "</div>"
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- ],
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- "text/plain": [
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- " Group Modality Level Metaname \\\n",
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- "0 BiasEvals Text Model weat \n",
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- "1 BiasEvals Text Model wefat \n",
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- "2 BiasEvals Text Dataset stereoset \n",
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- "3 BiasEvals Text Dataset crwospairs \n",
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- "4 BiasEvals Text Output honest \n",
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- "5 BiasEvals Image Model ieat \n",
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- "6 BiasEvals Image Dataset imagedataleak \n",
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- "7 BiasEvals Image Output stablebias \n",
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- "8 BiasEvals Image Output homoglyphbias \n",
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- "9 BiasEvals Audio Taxonomy (?) notmyvoice \n",
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- "10 BiasEvals Video Output videodiversemisinfo \n",
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- "11 Privacy NaN NaN NaN \n",
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- "\n",
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- " Suggested Evaluation \\\n",
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- "0 Word Embedding Association Test (WEAT) \n",
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- "1 Word Embedding Factual As\\nsociation Test (WEFAT) \n",
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- "2 StereoSet \n",
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- "3 Crow-S Pairs \n",
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- "4 HONEST: Measuring Hurtful Sentence Completion ... \n",
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- "5 Image Embedding Association Test (iEAT) \n",
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- "6 Dataset leakage and model leakage \n",
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- "7 Characterizing the variation in generated images \n",
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- "8 Effect of different scripts on text-to-image g... \n",
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- "9 Not My Voice! A Taxonomy of Ethical and Safety... \n",
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- "10 Diverse Misinformation: Impacts of Human Biase... \n",
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- "11 NaN \n",
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- "\n",
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- " What it is evaluating \\\n",
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- "0 Associations and word embeddings based on Impl... \n",
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- "1 Associations and word embeddings based on Impl... \n",
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- "2 Protected class stereotypes \n",
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- "3 Protected class stereotypes \n",
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- "4 Protected class stereotypes and hurtful language \n",
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- "5 Embedding associations \n",
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- "6 Gender and label bias \n",
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- "7 NaN \n",
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- "8 It evaluates generated images for cultural ste... \n",
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- "9 Lists harms of audio/speech generators \n",
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- "10 Human led evaluations of deepfakes to understa... \n",
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- "11 NaN \n",
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- "\n",
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- " Considerations \\\n",
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- "0 Although based in human associations, general ... \n",
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- "1 Although based in human associations, general ... \n",
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- "2 Automating stereotype detection makes distingu... \n",
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- "3 Automating stereotype detection makes distingu... \n",
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- "4 Automating stereotype detection makes distingu... \n",
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- "5 Although based in human associations, general ... \n",
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- "6 NaN \n",
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- "7 NaN \n",
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- "8 NaN \n",
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- "9 Not necessarily evaluation but a good source o... \n",
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- "10 Repr. harm, incite violence \n",
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- "11 NaN \n",
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- "\n",
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- " Link \\\n",
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- "0 Semantics derived automatically from language ... \n",
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- "1 Semantics derived automatically from language ... \n",
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- "2 StereoSet: Measuring stereotypical bias in pre... \n",
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- "3 CrowS-Pairs: A Challenge Dataset for Measuring... \n",
358
- "4 HONEST: Measuring Hurtful Sentence Completion ... \n",
359
- "5 Image Representations Learned With Unsupervise... \n",
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- "6 Balanced Datasets Are Not Enough: Estimating a... \n",
361
- "7 Stable bias: Analyzing societal representation... \n",
362
- "8 Exploiting Cultural Biases via Homoglyphs in T... \n",
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- "9 Not My Voice! A Taxonomy of Ethical and Safety... \n",
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- "10 Diverse Misinformation: Impacts of Human Biase... \n",
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- "11 NaN \n",
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- "\n",
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- " URL \\\n",
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- "0 https://researchportal.bath.ac.uk/en/publicati... \n",
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- "1 https://researchportal.bath.ac.uk/en/publicati... \n",
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- "2 https://arxiv.org/abs/2004.09456 \n",
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- "3 https://arxiv.org/abs/2010.00133 \n",
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- "4 https://aclanthology.org/2021.naacl-main.191.pdf \n",
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- "5 https://dl.acm.org/doi/abs/10.1145/3442188.344... \n",
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- "6 https://arxiv.org/abs/1811.08489 \n",
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- "7 https://arxiv.org/abs/2303.11408 \n",
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- "8 https://arxiv.org/pdf/2209.08891.pdf \n",
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- "9 https://arxiv.org/pdf/2402.01708.pdf \n",
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- "10 https://arxiv.org/abs/2210.10026 \n",
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- "11 NaN \n",
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- "\n",
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- " Screenshots Applicable Models Datasets \\\n",
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- "0 ['Images/WEAT1.png', 'Images/WEAT2.png'] NaN NaN \n",
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- "1 NaN NaN NaN \n",
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- "2 NaN NaN NaN \n",
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- "3 NaN NaN NaN \n",
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- "4 NaN NaN NaN \n",
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- "5 NaN NaN NaN \n",
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- "6 NaN NaN NaN \n",
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- "7 NaN NaN NaN \n",
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- "8 NaN NaN NaN \n",
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- "9 NaN NaN NaN \n",
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- "10 NaN NaN NaN \n",
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- "11 NaN NaN NaN \n",
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- "\n",
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- " Hashtags \n",
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- "0 NaN \n",
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- "1 NaN \n",
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- "2 NaN \n",
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- "4 NaN \n",
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- "9 NaN \n",
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- "10 NaN \n",
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- "11 NaN "
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- ]
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- },
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- "execution_count": 5,
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- "metadata": {},
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- "output_type": "execute_result"
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- }
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- ],
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- "source": [
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- "df"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 9,
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- "metadata": {},
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- "outputs": [],
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- "source": [
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- "import urllib.request\n",
426
- "from bs4 import BeautifulSoup\n",
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- "\n",
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- "from pypdf import PdfReader \n",
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- "from urllib.request import urlretrieve\n",
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- "\n",
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- "import pdfplumber\n",
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- "\n"
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- ]
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- },
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- {
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- "cell_type": "code",
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- "execution_count": 12,
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- "metadata": {},
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- "outputs": [
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- {
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- "name": "stdout",
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- "output_type": "stream",
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- "text": [
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- "https://researchportal.bath.ac.uk/en/publications/semantics-derived-automatically-from-language-corpora-necessarily\n",
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- "\n",
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- " Semantics derived automatically from language corpora contain human-like biases\n",
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- " — the University of Bath's research portal\n",
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- "https://researchportal.bath.ac.uk/en/publications/semantics-derived-automatically-from-language-corpora-necessarily\n",
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- "\n",
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- " Semantics derived automatically from language corpora contain human-like biases\n",
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- " — the University of Bath's research portal\n",
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- "https://arxiv.org/abs/1903.10561\n",
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- "[1903.10561] On Measuring Social Biases in Sentence Encoders\n",
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- "https://dl.acm.org/doi/abs/10.5555/3454287.3455472\n",
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- "Error\n",
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- "https://arxiv.org/abs/2004.09456\n",
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- "[2004.09456] StereoSet: Measuring stereotypical bias in pretrained language models\n",
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- "https://arxiv.org/abs/2010.00133\n",
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- "[2010.00133] CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models\n",
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- "https://aclanthology.org/2021.naacl-main.191.pdf\n"
461
- ]
462
- },
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- {
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- "name": "stderr",
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- "text": [
474
- "HONEST: Measuring Hurtful Sentence Completion in Language Models\n",
475
- "nan\n",
476
- "Error\n",
477
- "https://aclanthology.org/2022.findings-acl.165.pdf\n"
478
- ]
479
- },
480
- {
481
- "name": "stderr",
482
- "output_type": "stream",
483
- "text": [
484
- "Some characters could not be decoded, and were replaced with REPLACEMENT CHARACTER.\n"
485
- ]
486
- },
487
- {
488
- "name": "stdout",
489
- "output_type": "stream",
490
- "text": [
491
- "BBQ: A Hand-Built Bias Benchmark for Question Answering \n",
492
- "https://aclanthology.org/2022.findings-naacl.42.pdf\n"
493
- ]
494
- },
495
- {
496
- "name": "stderr",
497
- "output_type": "stream",
498
- "text": [
499
- "Some characters could not be decoded, and were replaced with REPLACEMENT CHARACTER.\n"
500
- ]
501
- },
502
- {
503
- "name": "stdout",
504
- "output_type": "stream",
505
- "text": [
506
- "On Measuring Social Biases in Prompt-Based Multi-Task Learning\n"
507
- ]
508
- }
509
- ],
510
- "source": [
511
- "def get_page_title(url):\n",
512
- " soup = BeautifulSoup(urllib.request.urlopen(url))\n",
513
- " return soup.title.string\n",
514
- "\n",
515
- "\n",
516
- "def extract_pdf_title(url):\n",
517
- " urlretrieve(url, 'temp.pdf')\n",
518
- " with pdfplumber.open('temp.pdf') as pdf:\n",
519
- " for page in pdf.pages:\n",
520
- " for line in page.extract_text().split('\\n'):\n",
521
- " return line\n",
522
- " return \"\"\n",
523
- "\n",
524
- " \n",
525
- " \n",
526
- "for url in df['URL'][:10]:\n",
527
- " try:\n",
528
- " print(url)\n",
529
- " title = get_page_title(url)\n",
530
- " print(title)\n",
531
- " except:\n",
532
- " try:\n",
533
- " title = extract_pdf_title(url)\n",
534
- " print(title)\n",
535
- " except:\n",
536
- " print(\"Error\")"
537
- ]
538
- },
539
- {
540
- "cell_type": "code",
541
- "execution_count": null,
542
- "metadata": {},
543
- "outputs": [],
544
- "source": []
545
- }
546
- ],
547
- "metadata": {
548
- "kernelspec": {
549
- "display_name": "gradio",
550
- "language": "python",
551
- "name": "python3"
552
- },
553
- "language_info": {
554
- "codemirror_mode": {
555
- "name": "ipython",
556
- "version": 3
557
- },
558
- "file_extension": ".py",
559
- "mimetype": "text/x-python",
560
- "name": "python",
561
- "nbconvert_exporter": "python",
562
- "pygments_lexer": "ipython3",
563
- "version": "3.12.2"
564
- }
565
- },
566
- "nbformat": 4,
567
- "nbformat_minor": 2
568
- }