mlsanityData to 7 Oct 2026

The Role of Interactive Visualization in Explaining (Large) NLP Models: from Data to Inference

arXiv 2301.04528 ↗First posted 11 Jan 2023cs.CL cs.HCcited by 9

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Abstract (arXiv)

With a constant increase of learned parameters, modern neural language models become increasingly more powerful. Yet, explaining these complex model's behavior remains a widely unsolved problem. In this paper, we discuss the role interactive visualization can play in explaining NLP models (XNLP). We motivate the use of visualization in relation to target users and common NLP pipelines. We also present several use cases to provide concrete examples on XNLP with visualization. Finally, we point out an extensive list of research opportunities in this field.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 25 of its 52 references that are in the map. First posted on arXiv 11 Jan 2023.

Builds on

25 of 52 references.

References · 25

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13 more
  1. 2019A Multiscale Visualization of Attention in the Transformer Modelcited by 292
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 6; 2025: 1; 2026: 1.

9 papers.

  1. 2024LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Modelscited by 29
  2. 2024Automatic Histograms: Leveraging Language Models for Text Dataset Explorationcited by 8
  3. 2024Understanding Large Language Model Behaviors through Interactive Counterfactual Generation and Analysiscited by 8
  4. 2024Talaria: Interactively Optimizing Machine Learning Models for Efficient Inferencecited by 6
  5. 2024Exploring Empty Spaces: Human-in-the-Loop Data Augmentationcited by 6
  6. 2024The Evolution of LLM Adoption in Industry Data Curation Practicescited by 6
  7. 2023Visualizing Linguistic Diversity of Text Datasets Synthesized by Large Language Modelscited by 4
  8. 2026RAGExplorer: A Visual Analytics System for the Comparative Diagnosis of RAG Systemscited by 2
  9. 2025A Visual Tool for Interactive Model Explanation using Sensitivity Analysiscited by 0