Omkar2118/datasets huggingface dataset:
RFUND-EN

English subset of RFUND

Introducing paper: PEneo: Unifying Line Extraction, Line Grouping, and Entity Linking for End-to-end Document Pair Extraction
TML1M
Full name: Table-MovieLens1M

Table-MovieLens1M (TML1M) is a relational table dataset derived from the classical MovieLens1M dataset. It consists of three tables: users, movies, and ratings. Notably, the movie table has been enriched with more comprehensive features. Additionally, the dataset defines a standard classification task focused on predicting user age ranges.

Introducing paper: rLLM: Relational Table Learning with LLMs
TLF2K
Full name: Table-LastFm2K

Table-LastFm2K (TLF2K) is a relational table dataset derived from the classical LastFM2K dataset. It contains three tables: artists, user_artists, and user_friends. Notably, the artists table has been enhanced with more detailed features, and the tags for each artist have been streamlined. The dataset also provides a standard classification task for music genre classification of artists.

Introducing paper: rLLM: Relational Table Learning with LLMs
TACM12K
Full name: Table-ACM12K

Table-ACM12K (TACM12K) is a relational table dataset derived from the ACM heterogeneous graph dataset. It includes four tables: papers, authors, citations, and writings. The paper table features attributes such as year, title, and abstract, while the author table includes name and affiliation details. Additionally, some feature completion has been performed for the papers. The dataset also defines a standard classification task for predicting the conference to which a paper belongs.

Introducing paper: rLLM: Relational Table Learning with LLMs
Flight Delay and Cancellation Dataset (2019-2023)

The dataset used in this study is obtained from the U.S. Department of Transportation, Bureau of Transportation Statistics from January 2019– August 2023 . It contains 32 attributes related to planned f light date-time, airline, planned origin and destination, cancellation and diversion status, overall delay, and delay due to individual components (carrier, weather, NAS, security, late aircraft), among others.