# Table Reasoning

Tessar is an advanced table reasoning model developed by SVECTOR, based on groundbreaking research that continuously expands the boundaries of neural table understanding.

ProTrix is a model designed for table and sentence contextual planning and reasoning, focusing on joint reasoning tasks involving tabular and textual data.

ReasTAP is a table reasoning-based pretrained model that injects table reasoning skills through synthetic reasoning examples and is fine-tuned on the WikiSQL dataset.

ReasTAP is a pre-trained model for table reasoning, which injects table reasoning skills through synthetic reasoning examples and is fine-tuned on the WikiTableQuestions dataset

TAPEX is a model that achieves table pretraining by learning neural SQL executors, based on the BART architecture, specifically designed for table reasoning tasks.

TAPEX is a table pre-training model that learns via neural SQL executor, based on the BART architecture, specifically designed for table reasoning tasks.

TAPEX is a model designed for table reasoning tasks, learning through neural SQL executors for table pretraining, based on the BART architecture.

TAPEX is a table pre-training model learned through neural SQL executors, based on the BART architecture, specifically designed for table reasoning tasks.

TAPEX is a table pre-training model that learns through a neural SQL executor, capable of handling table reasoning tasks.

TAPEX is a table pre-training model learned through a neural SQL executor, based on the BART architecture, specifically designed for table reasoning tasks.

TAPEX is a model that learns table reasoning capabilities through neural SQL executor training.

TAPAS is a BERT-like model based on the Transformer architecture, specifically designed for processing tabular data and related text. It is pre-trained through self-supervised learning on a massive collection of English Wikipedia tables and associated text.