mlsanityData to 7 Oct 2026

TART: An Open-Source Tool-Augmented Framework for Explainable Table-based Reasoning

arXiv 2409.11724 ↗First posted 18 Sep 2024cs.CLcited by 10

On the map: LLM reasoning → Knowledge- and tool-augmented reasoning

Abstract (arXiv)

Current Large Language Models (LLMs) exhibit limited ability to understand table structures and to apply precise numerical reasoning, which is crucial for tasks such as table question answering (TQA) and table-based fact verification (TFV). To address these challenges, we introduce our Tool-Augmented Reasoning framework for Tables (TART), which integrates LLMs with specialized tools. TART contains three key components: a table formatter to ensure accurate data representation, a tool maker to develop specific computational tools, and an explanation generator to maintain explainability. We also present the TOOLTAB dataset, a new benchmark designed specifically for training LLMs in table-tool integration. Our experiments indicate that TART achieves substantial improvements over existing methods (e.g., Chain-of-Thought) by improving both the precision of data processing and the clarity of the reasoning process. Notably, TART paired with CodeLlama achieves 90.0% of the accuracy of the closed-sourced LLM GPT-3.5-turbo, highlighting its robustness in diverse real-world scenarios. All the code and data are available at https://github.com/XinyuanLu00/TART.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. Builds on 50 of its 57 references that are in the map. First posted on arXiv 18 Sep 2024.

Builds on

50 of 57 references.

Closest ancestors · 9

Same direction, newest first

  1. 2024ProTrix: Building Models for Planning and Reasoning over Tables with Sentence Context4 Mar
  2. 2024SciAgent: Tool-augmented Language Models for Scientific Reasoning18 Feb
  3. 2024Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding9 Jan
  4. 2023Rethinking Tabular Data Understanding with Large Language Models27 Dec
  5. 2023TAP4LLM: Table Provider on Sampling, Augmenting, and Packing Semi-structured Data for Large Language Model Reasoning14 Dec
  6. 2023SCITAB: A Challenging Benchmark for Compositional Reasoning and Claim Verification on Scientific Tables22 May
  7. 2023Large Language Models are Versatile Decomposers: Decompose Evidence and Questions for Table-based Reasoning31 Jan
  8. 2022Large Language Models are few(1)-shot Table Reasoners13 Oct
  9. 2021HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation15 Aug

Other references · 41

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  4. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
  5. 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
  6. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,674
  7. 2023Code Llama: Open Foundation Models for Codecited by 2,105
  8. 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,880
  9. 2024DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligencecited by 1,154
  10. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
  11. 2022Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Taskscited by 1,057
  12. 2021Cross-Task Generalization via Natural Language Crowdsourcing Instructionscited by 696
29 more
  1. 2022PAL: Program-aided Language Modelscited by 635
  2. 2021FinQA: A Dataset of Numerical Reasoning over Financial Datacited by 552
  3. 2015Compositional Semantic Parsing on Semi-Structured Tablescited by 509
  4. 2020TAPAS: Weakly Supervised Table Parsing via Pre-trainingcited by 432
  5. 2019TabFact: A Large-scale Dataset for Table-based Fact Verificationcited by 425
  6. 2021TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Financecited by 402
  7. 2023Chameleon: Plug-and-Play Compositional Reasoning with Large Language Modelscited by 352
  8. 2022Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoningcited by 347
  9. 2023Large Language Models as Tool Makerscited by 293
  10. 2021Symbolic Knowledge Distillation: from General Language Models to Commonsense Modelscited by 270
  11. 2020HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Datacited by 263
  12. 2021TAPEX: Table Pre-training via Learning a Neural SQL Executorcited by 233
  13. 2021FeTaQA: Free-form Table Question Answeringcited by 174
  14. 2023Fact-Checking Complex Claims with Program-Guided Reasoningcited by 146
  15. 2023TableLlama: Towards Open Large Generalist Models for Tablescited by 136
  16. 2023ReAcTable: Enhancing ReAct for Table Question Answeringcited by 76
  17. 2024What Are Tools Anyway? A Survey from the Language Model Perspectivecited by 53
  18. 2022Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Taskscited by 42
  19. 2023Tab-CoT: Zero-shot Tabular Chain of Thoughtcited by 42
  20. 2022PASTA: Table-Operations Aware Fact Verification via Sentence-Table Cloze Pre-trainingcited by 41
  21. 2023Text2Analysis: A Benchmark of Table Question Answering with Advanced Data Analysis and Unclear Queriescited by 38
  22. 2021TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Datacited by 36
  23. 2021SemEval-2021 Task 9: Fact Verification and Evidence Finding for Tabular Data in Scientific Documents (SEM-TAB-FACTS)cited by 35
  24. 2020Program Enhanced Fact Verification with Verbalization and Graph Attention Networkcited by 29
  25. 2020LogicalFactChecker: Leveraging Logical Operations for Fact Checking with Graph Module Networkcited by 26
  26. 2024Husky: A Unified, Open-Source Language Agent for Multi-Step Reasoningcited by 16
  27. 2023API-Assisted Code Generation for Question Answering on Varied Table Structurescited by 14
  28. 2022Table-based Fact Verification with Self-adaptive Mixture of Expertscited by 12
  29. 2024Grounding Fallacies Misrepresenting Scientific Publications in Evidencecited by 7

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 5; 2026: 5.

10 papers.

  1. 2025A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systemscited by 108
  2. 2025Table-r1: Self-supervised and Reinforcement Learning for Program-based Table Reasoning in Small Language Modelscited by 7
  3. 2025What Level of Automation is "Good Enough"? A Benchmark of Large Language Models for Meta-Analysis Data Extractioncited by 6
  4. 2026Investigating Tool-Memory Conflicts in Tool-Augmented LLMscited by 5
  5. 2026CSRv2: Unlocking Ultra-Sparse Embeddingscited by 5
  6. 2025Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluationcited by 4
  7. 2025Mind the (Language) Gap: Towards Probing Numerical and Cross-Lingual Limits of LVLMscited by 2
  8. 2026Analyzing LLM Instruction Optimization for Tabular Fact Verificationcited by 1
  9. 2026ASTRA: Adaptive Semantic Tree Reasoning Architecture for Complex Table Question Answeringcited by 0
  10. 2026A Multi-Agent Approach for Claim Verification from Tabular Data Documentscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024A Survey of Table Reasoning with Large Language Models
  2. 2024TabSQLify: Enhancing Reasoning Capabilities of LLMs Through Table Decomposition
  3. 2026PARTAB: Partition-Aware Reasoning with Structured Evidence for Scalable Table Understanding
  4. 2025TReB: A Comprehensive Benchmark for Evaluating Table Reasoning Capabilities of Large Language Models
  5. 2025TableReasoner: Advancing Table Reasoning Framework with Large Language Models
  6. 2025RUST-BENCH: Benchmarking LLM Reasoning on Unstructured Text within Structured Tables
  7. 2026CRAFT: A Unified Counterfactual Reasoning Framework for Tabular Question Answering and Fact Verification
  8. 2024Tree-of-Table: Unleashing the Power of LLMs for Enhanced Large-Scale Table Understanding