Papers with language modelling tasks

2 papers
ReGLA: Refining Gated Linear Attention (2025.naacl-long)

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Challenge: Recent advances in Large Language Models (LLMs) are known for their computational and storage requirements due to the quadratic computation complexity of softmax attention.
Approach: They propose to reduce the quadratic computation complexity of softmax attention by using feature maps, normalization and the gating mechanism to improve performance.
Outcome: The proposed model outperforms existing gated linear attention models in extensive tasks including training from scratch and post-linearization with continual pre-training.
Reservoir Transformers (2021.acl-long)

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Challenge: Using random initialization, we show that some transformers obtain impressive performance even when some of the layers are frozen.
Approach: They propose to freeze transformer layers and use them to improve performance . they find that the transformers obtain impressive performance even when some of the layers are randomly initialized and never updated.
Outcome: The proposed model improves on translation and language modelling tasks even when some layers are frozen.

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