Update README.md

README.md

@@ -407,12 +407,9 @@ size_categories:
 # Dataset Card for `folktexts` <!-- omit in toc -->
 
 - [Dataset Details](#dataset-details)
-  - [Dataset Description](#dataset-description)
-  - [Dataset Sources](#dataset-sources)
 - [Uses](#uses)
 - [Dataset Structure](#dataset-structure)
 - [Dataset Creation](#dataset-creation)
-  - [Source Data](#source-data)
 - [Citation](#citation)
 - [More Information](#more-information)
 - [Dataset Card Authors](#dataset-card-authors)
@@ -467,15 +464,15 @@ eases customization, evaluation, and benchmarking with these datasets.**
 
 ## Dataset Details
 
-### Dataset Description
+### Dataset Description <!-- omit in toc -->
 
 - **Language(s) (NLP):** English
 - **License:** Code is licensed under the MIT license; Data license is governed by the U.S. Census Bureau [terms of service](https://www.census.gov/data/developers/about/terms-of-service.html).
 
-### Dataset Sources
+### Dataset Sources <!-- omit in toc -->
 
 - **Repository:** https://github.com/socialfoundations/folktexts
-- **Paper:** https://openreview.net/forum?id=qrZxL3Bto9
+- **Paper:** ["Evaluating language models as risk scores", Cruz et al., NeurIPS 2024.](https://arxiv.org/pdf/2407.14614)
 - **Data source:** [2018 American Community Survey Public Use Microdata Sample](https://www.census.gov/programs-surveys/acs/microdata/documentation/2018.html)
 
 ## Uses
@@ -492,18 +489,37 @@ as individual rows feature protected demographic attributes such as `sex` and
 
 <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
 
-[More Information Needed]
-**TODO!**
+**Description of dataset columns:**
+- `id`: A unique row identifier.
+- `description`: A textual description of an individual's features, following a bulleted-list format.
+- `instruction`: The instruction used for zero-shot LLM prompting (should be pre-appended to the row description).
+- `question`: A question relating to the task's target column.
+- `choices`: A list of two answer options relating to the above question.
+- `answer`: The correct answer from the above list of answer options.
+- `answer_key`: The correct answer key; i.e., `A` for the first choice, or `B` for the second choice.
+- `choice_question_prompt`: The full multiple-choice Q&A text string used for LLM prompting.
+- `numeric_question`: A version of the question that prompts for a *numeric output* instead of a *discrete choice output*.
+- `label`: The task's label. This is the correct output to the above numeric question.
+- `numeric_question_prompt`: The full numeric Q&A text string used for LLM prompting.
+- `<tabular-columns>`: All other columns correspond to the tabular features in this task. Each of these features will also appear in text form on the above description column.
+
+The dataset was randomly split in `training`, `test`, and `validation` data,
+following an 80%/10%/10% split.
+Only the `test` split should be used to evaluate zero-shot LLM performance.
+The `training` split can be used for fine-tuning, or for fitting traditional
+supervised ML models on the tabular columns for metric baselines.
+The `validation` split should be used for hyperparameter tuning, feature
+engineering or any other model improvement loop.
 
 ## Dataset Creation
 
-### Source Data
+### Source Data <!-- omit in toc -->
 
 The datasets are based on publicly available data from the American Community
 Survey (ACS) Public Use Microdata Sample (PUMS), namely the
 [2018 ACS 1-year PUMS files](https://www.census.gov/programs-surveys/acs/microdata/documentation.2018.html#list-tab-1370939201).
 
-#### Data Collection and Processing
+#### Data Collection and Processing <!-- omit in toc -->
 
 The categorical values were mapped to meaningful natural language
 representations using the `folktexts` package, which in turn uses the official
@@ -511,7 +527,7 @@ representations using the `folktexts` package, which in turn uses the official
 The data download and processing was aided by the `folktables` python package,
 which in turn uses the official US Census web API.
 
-#### Who are the source data producers?
+#### Who are the source data producers? <!-- omit in toc -->
 
 U.S. Census Bureau.