Updated docs and NeurIPS citation (#14)

* removed source folder - will be auto-generated * updated docs generation * updated folktext notebooks * updated landing page text * updated NeurIPS citation
socialfoundations · Oct 31, 2024 · c882bba · c882bba
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diff --git a/.github/workflows/python-docs.yml b/.github/workflows/python-docs.yml
@@ -24,7 +24,7 @@ jobs:
 
       - name: Install Sphinx and dependencies
         run: |
-          pip install -e ".[docs]"
+          pip install -e ".[docs,tests,cluster,apis]"
 
       - name: Install pandoc (external dependency)
         run: |

diff --git a/README.md b/README.md
@@ -230,14 +230,13 @@ This script uses sklearn's [`permutation_importance`](https://scikit-learn.org/s
 
 ## Citation
 
-```
-@misc{cruz2024evaluating,
+```bib
+@inproceedings{cruz2024evaluating,
     title={Evaluating language models as risk scores},
     author={Andr\'{e} F. Cruz and Moritz Hardt and Celestine Mendler-D\"{u}nner},
+    booktitle={The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
     year={2024},
-    eprint={2407.14614},
-    archivePrefix={arXiv},
-    primaryClass={cs.LG}
+    url={https://openreview.net/forum?id=qrZxL3Bto9}
 }
 ```
 

diff --git a/docs/index.rst b/docs/index.rst
@@ -12,21 +12,22 @@
 Welcome to :code:`folktexts`' documentation!
 ============================================
 
-The :code:`folktexts` package enables you to benchmark and evaluate LLMs as risk
-scores.
+The :code:`folktexts` package enables you to benchmark and evaluate 
+LLM-generated risk scores.
 
-We encode unrealizable tabular prediction tasks as natural-language text,
-and prompt LLMs for the probability of target variable being true.
+We encode unrealizable tabular prediction tasks as natural language text tasks,
+and prompt LLMs for the probability of a target variable being true.
 The correct solutions for each task often require expressing uncertainty, as the
 target variable is not uniquely determined by the input features.
 
-Folktexts is compatible with any huggingface transformer model.
+Folktexts is compatible with any huggingface transformer model and models 
+available through web APIs (e.g., OpenAI API).
 
 Five tabular data tasks are provided out-of-the-box, using the American
 Community Survey as a data source: `ACSIncome`, `ACSMobility`, `ACSTravelTime`, 
-`ACSEmployment`, and `ACSPublicCoverage`. These tasks follow the same name, feature 
-columns, and target columns as those put forth by `Ding et al. (2021)`_ in the
-`folktables`_ python package.
+`ACSEmployment`, and `ACSPublicCoverage`. These tasks follow the same name, 
+feature columns, and target columns as those put forth by `Ding et al. (2021)`_ 
+in the `folktables`_ python package.
 
 
 Full code available on the `GitHub repository`_, 
@@ -42,13 +43,32 @@ Check out the following sub-pages:
    Example notebooks <notebooks>
 
 
+Citing
+======
+
+The :code:`folktexts` package is the basis for the following `publication`_:
+
+.. code-block:: bib
+
+   @inproceedings{cruz2024evaluating,
+      title={Evaluating language models as risk scores},
+      author={Andr\'{e} F. Cruz and Moritz Hardt and Celestine Mendler-D\"{u}nner},
+      booktitle={The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
+      year={2024},
+      url={https://openreview.net/forum?id=qrZxL3Bto9}
+   }
+
+All additional supplementary materials are available in the `GitHub repository`_.
+
+
 Indices
 =======
 
 * :ref:`genindex`
 * :ref:`modindex`
 
 
+.. _publication: https://arxiv.org/abs/2407.14614
 .. _folktables: https://github.com/socialfoundations/folktables
 .. _Ding et al. (2021): https://arxiv.org/abs/2108.04884
 .. _GitHub repository: https://github.com/socialfoundations/folktexts

diff --git a/docs/notebooks.rst b/docs/notebooks.rst
@@ -7,3 +7,5 @@ Notebooks Gallery
    notebooks/custom-dataset-example.ipynb
    notebooks/custom-acs-task-example.ipynb
    notebooks/paper-plots-and-tables.ipynb
+   notebooks/minimal-example_web-API-model.ipynb
+   notebooks/parse-acs-results.ipynb
diff --git a/docs/source/folktexts.acs.rst b/docs/source/folktexts.acs.rst
diff --git a/docs/source/folktexts.cli.rst b/docs/source/folktexts.cli.rst
diff --git a/docs/source/folktexts.rst b/docs/source/folktexts.rst
diff --git a/docs/source/modules.rst b/docs/source/modules.rst
diff --git a/pyproject.toml b/pyproject.toml
@@ -32,7 +32,7 @@ classifiers = [
     "Programming Language :: Python :: 3.12",
 ]
 
-version = "0.0.22"
+version = "0.0.23"
 requires-python = ">=3.8"
 dynamic = [
     "readme",
@@ -42,7 +42,7 @@ dynamic = [
 
 [tool.setuptools]
 # NOTE! If you have multiple source directories, you can specify them here:
-packages = ["folktexts", "folktexts.acs", "folktexts.cli"]
+packages = ["folktexts", "folktexts.acs", "folktexts.cli", "folktexts.classifier"]
 include-package-data = true
 
 [tool.setuptools.dynamic]