Reference Summary: Forough Poursabzi, Researcher, Microsoft Research Presented at MLconf 2018 Abstract: Machine learning is increasingly used to ... 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?

25 Interpretability -

Forough Poursabzi, Researcher, Microsoft Research Presented at MLconf 2018 Abstract: Machine learning is increasingly used to ... 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 ...

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  • Forough Poursabzi, Researcher, Microsoft Research Presented at MLconf 2018 Abstract: Machine learning is increasingly used to ...
  • 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 ...
  • MIT 6.S897 Machine Learning for Healthcare, Spring 2019 Instructor: Peter Szolovits View the complete course: ...
  • A surprising fact about modern large language models is that nobody really knows how they work internally.

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25. Interpretability
An Introduction to Mechanistic Interpretability โ€“ Neel Nanda | IASEAI 2025
Lecture 25: Interpretability
What Matters Right Now In Mechanistic Interpretability?
The Dark Matter of AI [Mechanistic Interpretability]
What is interpretability?
Interpretability Beyond Feature Attribution
Manipulating and Measuring Model Interpretability
Interpretability and AI Scaling with Eric Michaud
A Walkthrough of Progress Measures for Grokking via Mechanistic Interpretability: What? (Part 1/3)
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25. Interpretability

25. Interpretability

MIT 6.S897 Machine Learning for Healthcare, Spring 2019 Instructor: Peter Szolovits View the complete course: ...

An Introduction to Mechanistic Interpretability โ€“ Neel Nanda | IASEAI 2025

An Introduction to Mechanistic Interpretability โ€“ Neel Nanda | IASEAI 2025

How can we reverse engineer what a neural network is doing? In this IASEAI '

Lecture 25: Interpretability

Lecture 25: Interpretability

Read more details and related context about Lecture 25: Interpretability.

What Matters Right Now In Mechanistic Interpretability?

What Matters Right Now In Mechanistic Interpretability?

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?

The Dark Matter of AI [Mechanistic Interpretability]

The Dark Matter of AI [Mechanistic Interpretability]

Take your personal data back with Incogni! Use code WELCHLABS at the link below and get 60% off an annual plan: ...

What is interpretability?

What is interpretability?

A surprising fact about modern large language models is that nobody really knows how they work internally. At Anthropic, the ...

Interpretability Beyond Feature Attribution

Interpretability Beyond Feature Attribution

Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim, Senior Research Scientist, Google Brain Presented at ...

Manipulating and Measuring Model Interpretability

Manipulating and Measuring Model Interpretability

Forough Poursabzi, Researcher, Microsoft Research Presented at MLconf 2018 Abstract: Machine learning is increasingly used to ...

Interpretability and AI Scaling with Eric Michaud

Interpretability and AI Scaling with Eric Michaud

Eric Michaud returns to the stream to talk about his recent work on

A Walkthrough of Progress Measures for Grokking via Mechanistic Interpretability: What? (Part 1/3)

A Walkthrough of Progress Measures for Grokking via Mechanistic Interpretability: What? (Part 1/3)

Part 1 of a walkthrough of our paper, Progress Measures for Grokking via Mechanistic