mlsanityData to 7 Oct 2026

The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models

arXiv 2008.05122 ↗First posted 12 Aug 2020cs.CLcited by 125

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Abstract (arXiv)

We present the Language Interpretability Tool (LIT), an open-source platform for visualization and understanding of NLP models. We focus on core questions about model behavior: Why did my model make this prediction? When does it perform poorly? What happens under a controlled change in the input? LIT integrates local explanations, aggregate analysis, and counterfactual generation into a streamlined, browser-based interface to enable rapid exploration and error analysis. We include case studies for a diverse set of workflows, including exploring counterfactuals for sentiment analysis, measuring gender bias in coreference systems, and exploring local behavior in text generation. LIT supports a wide range of models--including classification, seq2seq, and structured prediction--and is highly extensible through a declarative, framework-agnostic API. LIT is under active development, with code and full documentation available at https://github.com/pair-code/lit.

Key facts. Cited by 125 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Aug 2020.

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Citing papers per year: 2021: 27; 2022: 29; 2023: 24; 2024: 25; 2025: 8; 2026: 12.

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  1. 2024Gemma 2: Improving Open Language Models at a Practical Sizecited by 1,928
  2. 2021Post-hoc Interpretability for Neural NLP: A Surveycited by 155
  3. 2022Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Textcited by 154
  4. 2022Towards Faithful Model Explanation in NLP: A Surveycited by 129
  5. 2021Robustness Gym: Unifying the NLP Evaluation Landscapecited by 107
  6. 2023Frontier AI Regulation: Managing Emerging Risks to Public Safetycited by 95
  7. 2023Inseq: An Interpretability Toolkit for Sequence Generation Modelscited by 78
  8. 2022Black-box Prompt Learning for Pre-trained Language Modelscited by 70
  9. 2022Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Modelscited by 70
  10. 2021"Will You Find These Shortcuts?" A Protocol for Evaluating the Faithfulness of Input Salience Methods for Text Classificationcited by 66
  11. 2022TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversationscited by 65
  12. 2021Understanding the Effect of Out-of-distribution Examples and Interactive Explanations on Human-AI Decision Makingcited by 58
38 more
  1. 2022CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model Behaviorcited by 54
  2. 2021Explanation-Based Human Debugging of NLP Models: A Surveycited by 53
  3. 2022VL-InterpreT: An Interactive Visualization Tool for Interpreting Vision-Language Transformerscited by 53
  4. 2021ExplainaBoard: An Explainable Leaderboard for NLPcited by 50
  5. 2023AttentionViz: A Global View of Transformer Attentioncited by 50
  6. 2022An Empirical Study of Deep Learning Models for Vulnerability Detectioncited by 44
  7. 2022MultiViz: Towards Visualizing and Understanding Multimodal Modelscited by 36
  8. 2021Exploring the Role of BERT Token Representations to Explain Sentence Probing Resultscited by 29
  9. 2021Attention Approximates Sparse Distributed Memorycited by 29
  10. 2024LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Modelscited by 29
  11. 2021Dodrio: Exploring Transformer Models with Interactive Visualizationcited by 28
  12. 2022LM-Debugger: An Interactive Tool for Inspection and Intervention in Transformer-Based Language Modelscited by 28
  13. 2024Farsight: Fostering Responsible AI Awareness During AI Application Prototypingcited by 28
  14. 2022ferret: a Framework for Benchmarking Explainers on Transformerscited by 26
  15. 2022Human Interpretation of Saliency-based Explanation Over Textcited by 25
  16. 2023RELIC: Investigating Large Language Model Responses using Self-Consistencycited by 23
  17. 2021Automatic Construction of Evaluation Suites for Natural Language Generation Datasetscited by 18
  18. 2022A Unified Understanding of Deep NLP Models for Text Classificationcited by 18
  19. 2024Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challengescited by 18
  20. 2021LMdiff: A Visual Diff Tool to Compare Language Modelscited by 17
  21. 2024LLMCheckup: Conversational Examination of Large Language Models via Interpretability Tools and Self-Explanationscited by 16
  22. 2024LM Transparency Tool: Interactive Tool for Analyzing Transformer Language Modelscited by 16
  23. 2022Diagnosing AI Explanation Methods with Folk Concepts of Behaviorcited by 15
  24. 2024Position: Towards Bidirectional Human-AI Alignmentcited by 15
  25. 2021SummVis: Interactive Visual Analysis of Models, Data, and Evaluation for Text Summarizationcited by 13
  26. 2021T3-Vis: a visual analytic framework for Training and fine-Tuning Transformers in NLPcited by 11
  27. 2021Thermostat: A Large Collection of NLP Model Explanations and Analysis Toolscited by 11
  28. 2023NeuroX Library for Neuron Analysis of Deep NLP Modelscited by 11
  29. 2023InterroLang: Exploring NLP Models and Datasets through Dialogue-based Explanationscited by 11
  30. 2025Explainability in Practice: A Survey of Explainable NLP Across Various Domainscited by 11
  31. 2023R-U-SURE? Uncertainty-Aware Code Suggestions By Maximizing Utility Across Random User Intentscited by 10
  32. 2025Interpretation Meets Safety: A Survey on Interpretation Methods and Tools for Improving LLM Safetycited by 10
  33. 2021Clustering with UMAP: Why and How Connectivity Matterscited by 9
  34. 2022Beware the Rationalization Trap! When Language Model Explainability Diverges from our Mental Models of Languagecited by 9
  35. 2023The Role of Interactive Visualization in Explaining (Large) NLP Models: from Data to Inferencecited by 9
  36. 2023Text-Blueprint: An Interactive Platform for Plan-based Conditional Generationcited by 9
  37. 2024Detecting Hallucination and Coverage Errors in Retrieval Augmented Generation for Controversial Topicscited by 9
  38. 2021Does My Representation Capture X? Probe-Ablycited by 8

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