Update README.md

README.md

@@ -43,7 +43,7 @@ dataset_summary: '
 
   # Note: other available arguments include ''split'', ''max_samples'', etc
 
-  dataset = fouh.load_from_hub("harpreetsahota/CVPR_2024_Papers")
+  dataset = fouh.load_from_hub("Voxel51/CVPR_2024_Papers")
 
 
   # Launch the App
@@ -59,11 +59,11 @@ dataset_summary: '
 
 <!-- Provide a quick summary of the dataset. -->
 
+This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 2379 samples.
 
+The dataset consists of images of the first page for accepted papers to CVPR 2024, plus their abstract and other metadata.
 
-
-
-This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 2379 samples.
+![image/png](cvpr_papers_dataset.png)
 
 ## Installation
 
@@ -87,135 +87,47 @@ dataset = fouh.load_from_hub("harpreetsahota/CVPR_2024_Papers")
 session = fo.launch_app(dataset)
 ```
 
-
 ## Dataset Details
 
-### Dataset Description
+This is a dataset of the accepted papers for CVPR 2024. 
 
-<!-- Provide a longer summary of what this dataset is. -->
+The 2024 Conference on Computer Vision and Pattern Recognition (CVPR) received 11,532 valid paper submissions, 
+and only 2,719 were accepted, for an overall acceptance rate of about 23.6%.
 
+However, this dataset only has 2,379 papers. This is because its how many we were able to (easily) find papers for.
 
+### Dataset Description
 
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
+- **Curated by:** [Harpreet Sahota, Hacker-in-Residence at Voxel51](https://huggingface.co/harpreetsahota)
 - **Language(s) (NLP):** en
-- **License:** [More Information Needed]
-
-### Dataset Sources [optional]
-
-<!-- Provide the basic links for the dataset. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **License:** [CC-BY-ND-4.0](https://spdx.org/licenses/CC-BY-ND-4.0)
 
 ## Uses
 
-<!-- Address questions around how the dataset is intended to be used. -->
-
-### Direct Use
-
-<!-- This section describes suitable use cases for the dataset. -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-
-[More Information Needed]
+You can use this dataset to learn about the trends in research at this year's CVPR, and so much more!
 
 ## Dataset Structure
 
-<!-- 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. -->
+The dataset consists of the following:
 
-[More Information Needed]
+ - An image of the first page of the paper
+ - `title`: The title of the paper
+ - `authors_list`: The list of authors
+ - `abstract`: The abstract of the paper
+ - `arxiv_link`: Link to the paper on arXiv
+ - `other_link`: Link to the project page, if found
+ - `category_name`: The primary category this paper according to [arXiv taxonomy](https://arxiv.org/category_taxonomy)
+ - `all_categories`: All categories this paper falls into, according to arXiv taxonomy
+ - `keywords`: Extracted using GPT-4o
 
 ## Dataset Creation
 
-### Curation Rationale
-
-<!-- Motivation for the creation of this dataset. -->
-
-[More Information Needed]
-
-### Source Data
-
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-
-#### Data Collection and Processing
-
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-[More Information Needed]
-
-#### Who are the source data producers?
-
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-
-[More Information Needed]
-
-### Annotations [optional]
-
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-
-#### Annotation process
-
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-<!-- This section describes the people or systems who created the annotations. -->
-
-[More Information Needed]
-
-#### Personal and Sensitive Information
-
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Dataset Card Authors [optional]
-
-[More Information Needed]
+Generic code for building this dataset can be found [here](https://github.com/harpreetsahota204/CVPR-2024-Papers).
 
-## Dataset Card Contact
+This dataset was built using the following steps:
 
-[More Information Needed]
+- Scrape the CVPR 2024 website for accepted papers
+- Use DuckDuckGo to search for a link to the paper's abstract on arXiv
+- Use arXiv.py (python wrapper for the arXiv API) to extract the abstract, categories, and download the pdf for each paper
+- Use pdf2image to save image of papers first page
+- Use GPT-4o to extract keywords from abstract