What AI says about Captum
Captum is an open-source model interpretability library built on PyTorch to provide attribution methods for deep learning systems. It comes up when teams need explainable AI tools to investigate why models make specific predictions or to inspect internal workings like Transformer layers.
AI calls itmodel interpretable library,interpretable library,open-source,built specifically for pytorch,gradient-based attribution methods,useful
Since Jul 5Updated Nov 11, 2026Based on 18,043 AI answers
Reviewed by Dimitry Apollonsky
Mentioned in · Public index
<1%
of AI answers about Captum and its rivals · since Jul 5
Based on 18,043 AI answers
- ChatGPT<1%
- Google AI Mode<1%
How often AI mentions Captum
of AI answers about Captum and its rivals
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Sep 14OctNov 2
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Markets where AI mentions Captum
All marketsChatGPTGoogle AI Mode
Topics where AI mentions Captum
TopicMentioned in · on this topicRank
- Most mentionedMentioned in
- We are investigating why our model is confident but wrong. Who provides explainable AI (XAI) tools?on this questionSHAP is the most-mentioned brand67%
Excerpts where Captum appeared in the AI's answer
Google AI ModeOct 12, 2026, Google AI Mode Captum: Built specifically for PyTorch by Meta, Captum is designed for deep learning models.
ChatGPTSep 23, 2026, ChatGPT Captum — useful if your models are built with PyTorch; it provides techniques such as integrated gradients, saliency, and feature attribution.
- What's a good tool for debugging and visualizing the attention weights in a production Transformer model?on this questionBertViz is the most-mentioned brand11%
Excerpts where Captum appeared in the AI's answer
Google AI ModeJul 29, 2026, Google AI Mode Captum (by PyTorch) - What it is: A production-ready model interpretability and feature attribution framework.
Google AI ModeJul 29, 2026, Google AI Mode Integrated directly into inference pipelines to output token-level importance scores alongside the model's predictions, which can then be streamed to visualization dashboards like Captum Insights.
- What is the best tool for explaining black-box model predictions to non-technical stakeholders?on this questionSHAP is the most-mentioned brand7%
- What is the best tool for debugging and visualizing the internal workings of a production Transformer model?on this questionTransformerLens is the most-mentioned brand5%
- I need a tool for explaining black-box model predictions that can generate easy-to-understand reports for stakeholders.on this questionSHAP shares the lead for mentions with 1 more2%
Excerpts where Captum appeared in the AI's answer
Google AI ModeJul 22, 2026, Google AI Mode Captum: Designed for PyTorch models, Captum provides algorithms like Integrated Gradients to provide feature attributions.
Captum in AI answers
1 of 4
We are investigating why our model is confident but wrong. Who provides explainable AI (XAI) tools?
ChatGPTChatGPT· Sep 23, 2026
Captum — useful if your models are built with PyTorch; it provides techniques such as integrated gradients, saliency, and feature attribution.
Google AI ModeGoogle AI Mode· Oct 12, 2026
Captum: Built specifically for PyTorch by Meta, Captum is designed for deep learning models.
Sites AI cites
- 7%
- Explainable AI Frameworks: Navigating the Present Challenges and Unveiling Innovative Applications (opens in a new tab) · 5%
- XAI-IDS: Toward Proposing an Explainable Artificial Intelligence Framework for Enhancing Network Intrusion Detection Systems (opens in a new tab) · 1%
- Recent Applications of Explainable AI (XAI): A Systematic Literature Review (opens in a new tab) · 1%
- 7%
- The AI Governance Frontier Series Part 6 — Open-Source Tools and Initiatives for Responsible and Safe AI | by Adnan Masood, PhD. | Medium (opens in a new tab) · 2%
- Unlocking the Black Box: How to Make Your AI Model Explainable | by Farnaz Ghassemi Toudeshki | Medium (opens in a new tab) · 1%
- Medium (opens in a new tab) · 1%
- Visualize LLM Attention Layers with Captum: A Deep Dive | by Cristina R. | Medium (opens in a new tab) · 1%
- Medium (opens in a new tab) · 1%
- Beyond Accuracy: Why Explainable AI is Critical for Responsible Innovation? (opens in a new tab) · 1%
- 6%
- Do AI models know what they know? How explainable AI can ... (opens in a new tab) · 2%
- How to Interpret & Explain Your Black Box Models | Anaconda (opens in a new tab) · 1%
- How to Interpret & Explain Your Black Box Models (opens in a new tab) · 1%
- Model Interpretability with Captum - Narine Kokhilkyan (opens in a new tab) · 1%
- Explainable AI (XAI) Course: Counterfactual Explanations (opens in a new tab) · 1%
- 5%
- The role of explainable artificial intelligence in disease prediction (opens in a new tab) · 1%
- A Comprehensive Review of Explainable Artificial Intelligence (XAI) in Computer Vision - PMC (opens in a new tab) · 1%
- A comprehensive review of explainable artificial intelligence in healthcare methods, evaluation, and clinical integration - PMC (opens in a new tab) · 1%
- Demystifying Artificial Intelligence: A Systematic Review of Explainable Artificial Intelligence in Medical Imaging (opens in a new tab) · 1%
- Integrating Confidence, Difficulty, and Language Model Calibration for Better Explainability in Clinical Documents Coding: Applications of AI (opens in a new tab) · 1%
- 4%
- [2403.10415] Gradient based Feature Attribution in Explainable AI: A Technical Review (opens in a new tab) · 1%
- Explaining deep learning models for spoofing and deepfake detection with SHapley Additive exPlanations (opens in a new tab) · 1%
- Study on the Helpfulness of Explainable Artificial Intelligence (XAI) (opens in a new tab) · 1%
- Exploring the Impact of Explainable AI and Cognitive Capabilities on ... (opens in a new tab) · 1%
The page AI cites most often when it mentions Captum
Brands AI mentions
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