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Gated Transformer-XL

GTrXL

3 papers tagged archive 2025-07-28

Introduced by Emilio Parisotto et al. in Stabilizing Transformers for Reinforcement Learning

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

Gated Transformer-XL, or GTrXL, is a Transformer-based architecture for reinforcement learning. It introduces architectural modifications that improve the stability and learning speed of the original Transformer and XL variant. Changes include:

Placing the layer normalization on only the input stream of the submodules. A key benefit to this reordering is that it now enables an identity map from the input of the transformer at the first layer to the output of the transformer after the last layer. This is in contrast to the canonical transformer, where there are a series of layer normalization operations that non-linearly transform the state encoding.
Replacing residual connections with gating layers. The authors' experiments found that GRUs were the most effective form of gating.

Paper Source

Papers archive 2025-07-28

3 shown of 3, 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.

AGaLiTe: Approximate Gated Linear Transformers for Online Reinforcement Learning
24 Oct 2023 · 2 repositories · arXiv:2310.15719

Syntology ran 7 of 11 samples · 4 unverified
CoBERL: Contrastive BERT for Reinforcement Learning
12 Jul 2021 · 2 repositories · arXiv:2107.05431

Syntology ran 3 of 3 samples · 0 unverified
Stabilizing Transformers for Reinforcement Learning
13 Oct 2019 · 5 repositories · arXiv:1910.06764

Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)

Tasks archive 2025-07-28

9 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
Reinforcement Learning	3
reinforcement-learning	3
Reinforcement Learning (RL)	2
Diagnostic	1
General Reinforcement Learning	1
Language Modeling	1
Language Modelling	1
Machine Translation	1
Partially Observable Reinforcement Learning	1

Usage over time archive 2025-07-28

Papers per year the archive tags with this method, by the paper's archive date (3 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

RL Transformers

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