add minimal card template with citation info

README.md

@@ -2,8 +2,129 @@
 license: other
 license_name: cdla-permissive-2.0
 license_link: https://cdla.dev/permissive-2-0/
+tags:
+- document-ai
+pretty_name: KVP10k
+size_categories:
+- 10K<n<100K
 ---
 
 # KVP10k
 
-A Comprehensive Dataset for Key-Value Pair Extraction in Business Documents
+A Comprehensive Dataset for Key-Value Pair Extraction in Business Documents. 
+
+Abstract for the [paper](https://huggingface.co/papers/2405.00505) describing this dataset:
+
+> In recent years, the challenge of extracting information from business documents has emerged as a critical task, finding applications across numerous domains. This effort has attracted substantial interest from both industry and academy, highlighting its significance in the current technological landscape. Most datasets in this area are primarily focused on Key Information Extraction (KIE), where the extraction process revolves around extracting information using a specific, predefined set of keys. Unlike most existing datasets and benchmarks, our focus is on discovering key-value pairs (KVPs) without relying on predefined keys, navigating through an array of diverse templates and complex layouts. This task presents unique challenges, primarily due to the absence of comprehensive datasets and benchmarks tailored for non-predetermined KVP extraction. To address this gap, we introduce KVP10k , a new dataset and benchmark specifically designed for KVP extraction. The dataset contains 10707 richly annotated images. In our benchmark, we also introduce a new challenging task that combines elements of KIE as well as KVP in a single task. KVP10k sets itself apart with its extensive diversity in data and richly detailed annotations, paving the way for advancements in the field of information extraction from complex business documents.
+
+## Dataset Details
+
+### Dataset Description
+
+<!-- Provide a longer summary of what this dataset is. -->
+
+
+- **Curated by:** IBM
+- **License:** [cdla-permissive-2.0](https://cdla.dev/permissive-2-0/)
+
+### Dataset Sources [optional]
+
+<!-- Provide the basic links for the dataset. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## 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]
+
+## 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. -->
+
+[More Information Needed]
+
+## 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. -->
+
+
+## Citation
+
+**BibTeX:**
+
+```bibtext
+@misc{naparstek2024kvp10k,
+      title={KVP10k : A Comprehensive Dataset for Key-Value Pair Extraction in Business Documents}, 
+      author={Oshri Naparstek and Roi Pony and Inbar Shapira and Foad Abo Dahood and Ophir Azulai and Yevgeny Yaroker and Nadav Rubinstein and Maksym Lysak and Peter Staar and Ahmed Nassar and Nikolaos Livathinos and Christoph Auer and Elad Amrani and Idan Friedman and Orit Prince and Yevgeny Burshtein and Adi Raz Goldfarb and Udi Barzelay},
+      year={2024},
+      eprint={2405.00505},
+      archivePrefix={arXiv},
+      primaryClass={cs.IR}
+}
+```