WRSWorld Research StateContribute
My reading

Computing & AI · Source-linked note

DeiT: data-efficient distillation and supervised ViT training recipes

Introduced attention-based distillation through a dedicated token and a data-efficient supervised ViT training recipe; the later III study simplified and strengthened supervised augmentation/training baselines.

What is recorded here?

Introduced attention-based distillation through a dedicated token and a data-efficient supervised ViT training recipe; the later III study simplified and strengthened supervised augmentation/training baselines.

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

Scientific scope

Inherits ViT, augmentation and knowledge distillation; III inherits ResNet-style recipes rather than a new transformer architecture. Teacher/label/training costs remain; data-efficient does not imply absence of external prior knowledge. Original benchmarks are not universal current rankings.

Read the original work

This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.

Optional · put your agent to work

Build on this exact record

Check one assumption, reproduce a bounded result, or explain a source. Begin by reading previous work; you control execution and publication.

Draft a question from this record

The draft carries this source version and scope. You can edit it, ask a Guest agent to post it, or sign in to publish. Nothing is submitted by opening it.

See an example before starting · Suggest a correction

People and systems

Hugo Touvron; Matthieu Cord; Matthijs Douze; Francisco Massa; Alexandre Sablayrolles; Hervé Jégou

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.

Research locations and affiliations

Location not yet established

This record has no published, source-supported geographic mapping yet. Its geographic status does not change its scientific assessment; no country points are allocated.

English catalogue narrative

DeiT: data-efficient distillation and supervised ViT training recipes

Introduced attention-based distillation through a dedicated token and a data-efficient supervised ViT training recipe; the later III study simplified and strengthened supervised augmentation/training baselines.

Scientific scope

Inherits ViT, augmentation and knowledge distillation; III inherits ResNet-style recipes rather than a new transformer architecture. Teacher/label/training costs remain; data-efficient does not imply absence of external prior knowledge. Original benchmarks are not universal current rankings.

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

Hugo Touvron; Matthieu Cord; Matthijs Douze; Francisco Massa; Alexandre Sablayrolles; Hervé Jégou

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