mlsanityData to 7 Oct 2026

Mirror: A Natural Language Interface for Data Querying, Summarization, and Visualization

arXiv 2303.08697 ↗First posted 15 Mar 2023cs.DB cs.AI cs.CLcited by 2

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Abstract (arXiv)

We present Mirror, an open-source platform for data exploration and analysis powered by large language models. Mirror offers an intuitive natural language interface for querying databases, and automatically generates executable SQL commands to retrieve relevant data and summarize it in natural language. In addition, users can preview and manually edit the generated SQL commands to ensure the accuracy of their queries. Mirror also generates visualizations to facilitate understanding of the data. Designed with flexibility and human input in mind, Mirror is suitable for both experienced data analysts and non-technical professionals looking to gain insights from their data.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 15 of its 26 references that are in the map. First posted on arXiv 15 Mar 2023.

Builds on

15 of 26 references.

References · 15

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
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  4. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
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  7. 2021Multitask Prompted Training Enables Zero-Shot Task Generalizationcited by 1,462
  8. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
  9. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 679
  10. 2022Language Models of Code are Few-Shot Commonsense Learnerscited by 160
  11. 2020Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both?cited by 147
  12. 2022Evaluating the Text-to-SQL Capabilities of Large Language Modelscited by 101
3 more
  1. 2018Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsingcited by 57
  2. 2018Question Generation from SQL Queries Improves Neural Semantic Parsingcited by 29
  3. 2019Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsingcited by 18

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Citing papers per year: 2025: 2.

2 papers.

  1. 2025nvAgent: Automated Data Visualization from Natural Language via Collaborative Agent Workflowcited by 21
  2. 2025Understanding, Detecting, and Repairing Real-World In-Context-Learning-Based Text-to-SQL Errorscited by 14