XNLI: Explaining and Diagnosing NLI-based Visual Data Analysis
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Abstract (arXiv)
Natural language interfaces (NLIs) enable users to flexibly specify analytical intentions in data visualization. However, diagnosing the visualization results without understanding the underlying generation process is challenging. Our research explores how to provide explanations for NLIs to help users locate the problems and further revise the queries. We present XNLI, an explainable NLI system for visual data analysis. The system introduces a Provenance Generator to reveal the detailed process of visual transformations, a suite of interactive widgets to support error adjustments, and a Hint Generator to provide query revision hints based on the analysis of user queries and interactions. Two usage scenarios of XNLI and a user study verify the effectiveness and usability of the system. Results suggest that XNLI can significantly enhance task accuracy without interrupting the NLI-based analysis process.
Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 26 of its 60 references that are in the map. First posted on arXiv 25 Jan 2023.
Builds on
26 of 60 references.
References · 26
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2021AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Promptscited by 265
- 2020NL4DV: A Toolkit for Generating Analytic Specifications for Data Visualization from Natural Language Queriescited by 73
- 2021Towards Natural Language Interfaces for Data Visualization: A Surveycited by 58
- 2021Collecting and Characterizing Natural Language Utterances for Specifying Data Visualizationscited by 31
- 2021nvBench: A Large-Scale Synthesized Dataset for Cross-Domain Natural Language to Visualization Taskcited by 27
- 2019FlowSense: A Natural Language Interface for Visual Data Exploration within a Dataflow Systemcited by 25
- 2017Iris: A Conversational Agent for Complex Taskscited by 22
- 2022Towards Natural Language-Based Visualization Authoringcited by 22
- 2021Snowy: Recommending Utterances for Conversational Visual Analysiscited by 14
- 2020InChorus: Designing Consistent Multimodal Interactions for Data Visualization on Tablet Devicescited by 12
- 2022Facilitating Conversational Interaction in Natural Language Interfaces for Visualizationcited by 12
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- 2022Sporthesia: Augmenting Sports Videos Using Natural Languagecited by 11
- 2020Quda: Natural Language Queries for Visual Data Analyticscited by 9
- 2022Persua: A Visual Interactive System to Enhance the Persuasiveness of Arguments in Online Discussioncited by 7
- 2020Interweaving Multimodal Interaction with Flexible Unit Visualizations for Data Explorationcited by 6
- 2022Beyond Interestingness: Semantic and Context-Aware Natural Language Query Recommendations for Visual Data Analysiscited by 6
- 2018Explaining Queries over Web Tables to Non-Expertscited by 5
- 2020Touch? Speech? or Touch and Speech? Investigating Multimodal Interaction for Visual Network Exploration and Analysiscited by 5
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Citing papers per year: 2023: 5; 2024: 8; 2025: 3; 2026: 2.
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- 2024DataLab: A Unified Platform for LLM-Powered Business Intelligence3 Dec 2024
- 2024Data Analysis in the Era of Generative AI27 Sep 2024
- 2024Prismatic: Interactive Multi-View Cluster Analysis of Concept Stocks14 Feb 2024
- 2023JarviX: A LLM No code Platform for Tabular Data Analysis and Optimization3 Dec 2023
- 2023PromptMagician: Interactive Prompt Engineering for Text-to-Image Creation18 Jul 2023
- 2023ScrollTimes: Tracing the Provenance of Paintings as a Window into History15 Jun 2023
- 2023Towards an Understanding and Explanation for Mixed-Initiative Artificial Scientific Text Detection11 Apr 2023