mlsanityData to 7 Oct 2026

MURRE: Multi-Hop Table Retrieval with Removal for Open-Domain Text-to-SQL

arXiv 2402.10666 ↗First posted 16 Feb 2024cs.CLcited by 7

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Abstract (arXiv)

The open-domain text-to-SQL task aims to retrieve question-relevant tables from massive databases and generate SQL. However, the performance of current methods is constrained by single-hop retrieval, and existing multi-hop retrieval of open-domain question answering is not directly applicable due to the tendency to retrieve tables similar to the retrieved ones but irrelevant to the question. Since the questions in text-to-SQL usually contain all required information, while previous multi-hop retrieval supplements the questions with retrieved documents. Therefore, we propose the multi-hop table retrieval with removal (MURRE), which removes previously retrieved information from the question to guide the retriever towards unretrieved relevant tables. Our experiments on two open-domain text-to-SQL datasets demonstrate an average improvement of 5.7% over the previous state-of-the-art results.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 22 of its 39 references that are in the map. First posted on arXiv 16 Feb 2024.

Builds on

22 of 39 references.

References · 22

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  2. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
  3. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
  4. 2022Measuring and Narrowing the Compositionality Gap in Language Modelscited by 1,054
  5. 2022Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questionscited by 911
  6. 2023Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLscited by 667
  7. 2023Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluationcited by 378
  8. 2023Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergycited by 343
  9. 2023Self-Evaluation Guided Beam Search for Reasoningcited by 195
  10. 2023RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQLcited by 191
  11. 2019CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databasescited by 180
  12. 2020Answering Complex Open-Domain Questions with Multi-Hop Dense Retrievalcited by 160
10 more
  1. 2023Take a Step Back: Evoking Reasoning via Abstraction in Large Language Modelscited by 157
  2. 2019SParC: Cross-Domain Semantic Parsing in Contextcited by 141
  3. 2022Dense Text Retrieval based on Pretrained Language Models: A Surveycited by 136
  4. 2023Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-Incited by 71
  5. 2023End-to-End Beam Retrieval for Multi-Hop Question Answeringcited by 35
  6. 2021Awakening Latent Grounding from Pretrained Language Models for Semantic Parsingcited by 28
  7. 2023CRUSH4SQL: Collective Retrieval Using Schema Hallucination For Text2SQLcited by 23
  8. 2022UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQLcited by 20
  9. 2024Using LLM to select the right SQL Query from candidatescited by 12
  10. 2022How Does Beam Search improve Span-Level Confidence Estimation in Generative Sequence Labeling?cited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 3.

7 papers.

  1. 2025Can LLMs Help You at Work? A Sandbox for Evaluating LLM Agents in Enterprise Environmentscited by 15
  2. 2025Are We Asking the Right Questions? On Ambiguity in Natural Language Queries for Tabular Data Analysiscited by 3
  3. 2025Exploring Multi-Table Retrieval Through Iterative Searchcited by 2
  4. 2025Planning Agents on an Ego-Trip: Leveraging Hybrid Ego-Graph Ensembles for Improved Tool Retrieval in Enterprise Task Planningcited by 1
  5. 2026Fine-Grained Table Retrieval Through the Lens of Complex Queriescited by 1
  6. 2026Toward Multi-Database Query Reasoning for Text2Cyphercited by 0
  7. 2026Retrieve Only Relevant Tables Whether Few or Many: Adaptive Table Retrieval Methodcited by 0