Methods › Computer Vision › Image Model Blocks › XCiT Layer

XCiT Layer

4 papers tagged archive 2025-07-28

Introduced by Alaaeldin El-Nouby et al. in XCiT: Cross-Covariance Image Transformers

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

An XCiT Layer is the main building block of the XCiT architecture which uses a cross-covariance attention operator as its principal operation. The XCiT layer consists of three main blocks, each preceded by LayerNorm and followed by a residual connection: (i) the core cross-covariance attention (XCA) operation, (ii) the local patch interaction (LPI) module, and (iii) a feed-forward network (FFN). By transposing the query-key interaction, the computational complexity of XCA is linear in the number of data elements N, rather than quadratic as in conventional self-attention.

PaperSource

Papers archive 2025-07-28

4 shown of 4, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

10 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Image Classification3
image-classification2
Decoder1
Instance Segmentation1
Object Detection1
Pose Estimation1
Quantization1
Self-Supervised Image Classification1
Semantic Segmentation1
object-detection1

Usage over time archive 2025-07-28

Papers per year tagged with XCiT Layer: 2021 to 2022, peak 2 2 0 2021: 2 papers 2021 2022: 2 papers 2022
Papers per year the archive tags with this method, by the paper's archive date (4 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Image Model Blocks

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