Methods › General › Attention Modules › DeLighT Block
DeLighT Block
Introduced by Sachin Mehta et al. in DeLighT: Deep and Light-weight Transformer
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
A DeLighT Block is a block used in the DeLighT transformer architecture. It uses a DExTra transformation to reduce the dimensionality of the vectors entered into the attention layer, where a single-headed attention module is used. Since the DeLighT block learns wider representations of the input across different layers using DExTra, it enables the authors to replace multi-head attention with single-head attention. This is then followed by a light-weight FFN which, rather than expanding the dimension (as in normal Transformers which widen to a dimension 4x the size), imposes a bottleneck and squeezes the dimensions. Again, the reason for this is that the DExTra transformation has already incorporated wider representations so we can squeeze instead at this layer.
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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DeLighT: Deep and Light-weight Transformer 3 Aug 2020 · 2 repositories · arXiv:2008.00623Syntology ran 0 of 3 samples · 3 unverified
Tasks archive 2025-07-28
4 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 |
|---|---|
| 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
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