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Last Updated: June 6, 2026
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25. Interpretability
6,474 views • Live Report
Lecture 25: Interpretability
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An Introduction to Mechanistic Interpretability – Neel Nanda | IASEAI 2025
7,318 views • Live Report
What Matters Right Now In Mechanistic Interpretability?
6,642 views • Live Report
Introduction to 25 Interpretability
MIT 6.S897 Machine Learning for Healthcare, Spring 2019 Instructor: Peter Szolovits View the complete course: ... How can we reverse engineer what a neural network is doing? In this IASEAI ' This is a talk I gave to my MATS 9.0 training scholars about the big picture of mech interp - as of Oct 2025, what had changed? Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim, Senior Research Scientist, Google Brain Presented at ... Take your personal data back with Incogni! Use code WELCHLABS at the link below and get 60% off an annual plan: ... Forough Poursabzi, Researcher, Microsoft Research Presented at MLconf 2018 Abstract: Machine learning is increasingly used to ...
Dhanya Sridhar (IVADO + Université de Montréal + Mila) ... This video was recorded in San Francisco on February 4th, 2019. Bio: Patrick Hall is senior director for data science products at ... This talk was recorded at NDC AI in Oslo, Norway. Attend the next NDC ... What's happening inside an AI model as it thinks? Why are AI models sycophantic, and why do they hallucinate? Are AI models ... How can we use the language of causality to understand and edit the internal mechanisms of AI models? Atticus Geiger ... A surprising fact about modern large language models is that nobody really knows how they work internally. At Anthropic, the ...
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May 13, 2025 Large language models do many things, and it's not clear from black-box interactions how they do them. We will ...
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25. Interpretability
Lecture 25: Interpretability
An Introduction to Mechanistic Interpretability – Neel Nanda | IASEAI 2025
What Matters Right Now In Mechanistic Interpretability?
![[CoLoRAI 25] Compositionality Unlocks Deep Interpretable Models](https://i0.wp.com/ytimg.googleusercontent.com/vi/yUGZVPJlvzY/mqdefault.jpg?resize=320,180)
[CoLoRAI 25] Compositionality Unlocks Deep Interpretable Models
Interpretability Beyond Feature Attribution
![The Dark Matter of AI [Mechanistic Interpretability]](https://i0.wp.com/ytimg.googleusercontent.com/vi/UGO_Ehywuxc/mqdefault.jpg?resize=320,180)
The Dark Matter of AI [Mechanistic Interpretability]
Manipulating and Measuring Model Interpretability
Causal Representation Learning: A Natural Fit for Mechanistic Interpretability
Machine Learning Interpretability, Patrick Hall - H2O World San Francisco
Between the Layers– Interpreting Large Language Models - Michelle Frost - NDC AI 2025
Part 2: 5. Interpretability
Interpretability: Understanding how AI models think
Causal Mechanistic Interpretability - Atticus Geiger
What is interpretability?
Systor 25' Keynote: Prof. Nir Shavit - Towards Combinatorial Interpretability of Neural Computation
