Methods › Computer Vision › Convolutions › LightConv
Lightweight Convolution
LightConv
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
LightConv is a type of depthwise convolution for sequential modelling which shares certain output channels and whose weights are normalized across the temporal dimension using a softmax. Compared to self-attention, LightConv has a fixed context window and it determines the importance of context elements with a set of weights that do not change over time steps. LightConv computes the following for the i-th element in the sequence and output channel c:
LightConv(X, W_(ceil(cH/d),:), i, c) = DepthwiseConv(X,softmax(W_(ceil(cH/d),:)), i, c)
Papers archive 2025-07-28
1 shown of 1, 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.
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Pay Less Attention with Lightweight and Dynamic Convolutions 29 Jan 2019 · 3 repositories · arXiv:1901.10430
Tasks archive 2025-07-28
5 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Abstractive Text Summarization | 1 |
| Language Modeling | 1 |
| Language Modelling | 1 |
| Machine Translation | 1 |
| Translation | 1 |
Usage over time archive 2025-07-28
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
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections