| license: mit | |
| pretty_name: TopBench | |
| task_categories: | |
| - tabular-classification | |
| - tabular-regression | |
| - question-answering | |
| language: | |
| - en | |
| tags: | |
| - tabular | |
| - benchmark | |
| - predictive-reasoning | |
| - llm | |
| # TopBench Dataset | |
| TopBench is a benchmark for predictive reasoning over tabular data. Each example asks a model to infer an unobserved outcome, decision, treatment effect, or ranked/filtering result from historical tables and a natural-language query. | |
| ## Layout | |
| ```text | |
| single_point_prediction/ | |
| decision_making/ | |
| treatment_effect_analysis/ | |
| ranking_and_filtering/ | |
| ``` | |
| Each task directory contains dataset folders with `history.csv`, query JSON files, and metadata. The `ranking_and_filtering` task also includes `current.csv` and expects structured CSV outputs. | |
| Use the code release at https://github.com/LAMDA-Tabular/TopBench for validation, inference, evaluation, and the predict-only baseline. | |