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Concept bottleneck models with editable intermediate concepts

Trains prediction through an explicitly supervised concept bottleneck using independent, sequential or joint losses, allowing predicted concepts to be corrected before the final output.

What is recorded here?

Trains prediction through an explicitly supervised concept bottleneck using independent, sequential or joint losses, allowing predicted concepts to be corrected before the final output.

Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.

Scientific scope

General computing architecture only; medical application is excluded. Requires training-time concept annotations, and modifying a predicted concept inside a model is not intervening on the real-world causal variable. Earlier attribute-based systems are acknowledged, not claimed newly invented. First three authors explicitly equal.

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People and systems

Pang Wei Koh; Thao Nguyen; Yew Siang Tang; Stephen Mussmann; Emma Pierson; Been Kim; Percy Liang

Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.

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English catalogue narrative

Concept bottleneck models with editable intermediate concepts

Trains prediction through an explicitly supervised concept bottleneck using independent, sequential or joint losses, allowing predicted concepts to be corrected before the final output.

Scientific scope

General computing architecture only; medical application is excluded. Requires training-time concept annotations, and modifying a predicted concept inside a model is not intervening on the real-world causal variable. Earlier attribute-based systems are acknowledged, not claimed newly invented. First three authors explicitly equal.

Reading status

This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.

People and systems

Pang Wei Koh; Thao Nguyen; Yew Siang Tang; Stephen Mussmann; Emma Pierson; Been Kim; Percy Liang

Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.

Original sources