HyperAIHyperAI

Command Palette

Search for a command to run...

Console

Semantic Parsing On Wikitablequestions

Metrics

Accuracy (Dev)
Accuracy (Test)

Results

Performance results of various models on this benchmark

Paper Title
ARTEMIS-DA-80.8ARTEMIS-DA: An Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics
TabLaP/76.6Accurate and Regret-aware Numerical Problem Solver for Tabular Question Answering
SynTQA (GPT)-74.4SynTQA: Synergistic Table-based Question Answering via Mixture of Text-to-SQL and E2E TQA
Mix SC/73.6Rethinking Tabular Data Understanding with Large Language Models
SynTQA (RF)/71.6SynTQA: Synergistic Table-based Question Answering via Mixture of Text-to-SQL and E2E TQA
CABINET/69.1CABINET: Content Relevance based Noise Reduction for Table Question Answering
Chain-of-Table/67.31Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
Tab-PoT/66.78Efficient Prompting for LLM-based Generative Internet of Things
Dater64.865.9Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning
LEVER64.665.8LEVER: Learning to Verify Language-to-Code Generation with Execution
TabSQLify (col+row)-64.7TabSQLify: Enhancing Reasoning Capabilities of LLMs Through Table Decomposition
Binder65.064.6Binding Language Models in Symbolic Languages
OmniTab-Large62.563.3OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering
NormTab (Targeted) + SQL-61.20NormTab: Improving Symbolic Reasoning in LLMs Through Tabular Data Normalization
ReasTAP-Large59.758.7ReasTAP: Injecting Table Reasoning Skills During Pre-training via Synthetic Reasoning Examples
TAPEX-Large57.057.5TAPEX: Table Pre-training via Learning a Neural SQL Executor
MAPO + TABERTLarge (K = 3)52.251.8TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data
T5-3b(UnifiedSKG)50.6549.29UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models
TAPAS-Large (pre-trained on SQA)/48.8TAPAS: Weakly Supervised Table Parsing via Pre-training
Structured Attention43.744.5Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs
0 of 21 row(s) selected.
Semantic Parsing On Wikitablequestions | SOTA | HyperAI