tabfact.

TableMaster with GPT-4o backbone. Adaptive reasoning with table verbalization. From paper: TableMaster: A Recipe to Advance Table Understanding with Language Models

From paper: ARTEMIS-DA: An Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics

From paper: Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning

STaR-8B with Qwen3-8B backbone. Slow-thinking via SFT+RFT+uncertainty quantification. From paper: STaR: Towards Effective and Stable Table Reasoning via Slow-Thinking Large Language Models

From paper: PASTA: Table-Operations Aware Fact Verification via Sentence-Table Cloze Pre-training

T-REX using Phi-4 (14B) with chain-of-thought and naturalized text table format. From paper: T-REX: Table – Refute or Entail eXplainer

PoTable with GPT-4o-mini backbone on TabFact small test set. Stage-oriented plan-then-execute reasoning. From paper: PoTable: Programming Standardly on Table-based Reasoning Like a Human Analyst

From paper: Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding

From paper: Binding Language Models in Symbolic Languages

From paper: Efficient Prompting for LLM-based Generative Internet of Things

From paper: ReasTAP: Injecting Table Reasoning Skills During Pre-training via Synthetic Reasoning Examples

From paper: TAPEX: Table Pre-training via Learning a Neural SQL Executor

RePanda using fine-tuned DeepSeek-coder-7B on PanTabFact dataset with pandas-based structured reasoning. From paper: RePanda: Pandas-powered Tabular Verification and Reasoning

From paper: UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models

From paper: Table-based Fact Verification with Salience-aware Learning

From paper: Understanding tables with intermediate pre-training

From paper: TabSQLify: Enhancing Reasoning Capabilities of LLMs Through Table Decomposition

From paper: NormTab: Improving Symbolic Reasoning in LLMs Through Tabular Data Normalization

From paper: TabFact: A Large-scale Dataset for Table-based Fact Verification

From paper: TabFact: A Large-scale Dataset for Table-based Fact Verification

From paper: ReasTAP: Injecting Table Reasoning Skills During Pre-training via Synthetic Reasoning Examples

From paper: TAPEX: Table Pre-training via Learning a Neural SQL Executor

From paper: UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models

From paper: Table-based Fact Verification with Salience-aware Learning

From paper: Understanding tables with intermediate pre-training

From paper: TabFact: A Large-scale Dataset for Table-based Fact Verification

From paper: TabFact: A Large-scale Dataset for Table-based Fact Verification