mlsanityData to 14 Oct 2026

Team Anotheroption at SemEval-2025 Task 8: Bridging the Gap Between Open-Source and Proprietary LLMs in Table QA

arXiv 2506.09657 ↗First posted 11 Jun 2025cs.CLcited by 1

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Abstract (arXiv)

This paper presents a system developed for SemEval 2025 Task 8: Question Answering (QA) over tabular data. Our approach integrates several key components: text-to-SQL and text-to-code generation modules, a self-correction mechanism, and a retrieval-augmented generation (RAG). Additionally, it includes an end-to-end (E2E) module, all orchestrated by a large language model (LLM). Through ablation studies, we analyzed the effects of different parts of our pipeline and identified the challenges that are still present in this field. During the evaluation phase of the competition, our solution achieved an accuracy of 80%, resulting in a top-13 ranking among the 38 participating teams. Our pipeline demonstrates a significant improvement in accuracy for open-source models and achieves a performance comparable to proprietary LLMs in QA tasks over tables. The code is available at GitHub repository.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 22 of its 45 references that are in the map. First posted on arXiv 11 Jun 2025.

Builds on

22 of 45 references.

References · 22

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2024The Llama 3 Herd of Modelscited by 14,715
  3. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,234
  4. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,212
  5. 2022ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoningcited by 1,479
  6. 2024Qwen2.5-Coder Technical Reportcited by 1,203
  7. 2021Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigmcited by 606
  8. 2021FeTaQA: Free-form Table Question Answeringcited by 175
  9. 2024Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Surveycited by 159
  10. 2024Summary of a Haystack: A Challenge to Long-Context LLMs and RAG Systemscited by 87
  11. 2024TICKing All the Boxes: Generated Checklists Improve LLM Evaluation and Generationcited by 68
  12. 2022A Survey on Table Question Answering: Recent Advancescited by 41
10 more
  1. 2023Open-WikiTable: Dataset for Open Domain Question Answering with Complex Reasoning over Tablecited by 40
  2. 2024Language Modeling on Tabular Data: A Survey of Foundations, Techniques and Evolutioncited by 19
  3. 2024A Theoretical Understanding of Chain-of-Thought: Coherent Reasoning and Error-Aware Demonstrationcited by 13
  4. 2025Confidence Estimation for Error Detection in Text-to-SQL Systemscited by 11
  5. 2024Navigating Tabular Data Synthesis Research: Understanding User Needs and Tool Capabilitiescited by 8
  6. 2024MFORT-QA: Multi-hop Few-shot Open Rich Table Question Answeringcited by 7
  7. 2022TableQuery: Querying tabular data with natural languagecited by 5
  8. 2024Think Beyond Size: Adaptive Prompting for More Effective Reasoningcited by 2
  9. 2024LLMs and the Madness of Crowdscited by 2
  10. 2024Training Table Question Answering via SQL Query Decompositioncited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026PARTAB: Partition-Aware Reasoning with Structured Evidence for Scalable Table Understandingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Agentic LLMs for Question Answering over Tabular Data
  2. 2026Accurate Table Question Answering with Accessible LLMs
  3. 2024T-RAG: Lessons from the LLM Trenches
  4. 2024Exploring the Impact of Table-to-Text Methods on Augmenting LLM-based Question Answering with Domain Hybrid Data
  5. 2022End-to-End Table Question Answering via Retrieval-Augmented Generation
  6. 2024TAT-LLM: A Specialized Language Model for Discrete Reasoning over Tabular and Textual Data
  7. 2024TabSQLify: Enhancing Reasoning Capabilities of LLMs Through Table Decomposition
  8. 2025Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation