5 stories tagged with #transformer-models, in publish-time order across the WeSearch catalog. Tag pages update as new stories ingest.
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Exact Linear Attention
This paper introduces Exact Linear Attention (ELA), a mechanism that achieves linear computational complexity for Transformer attention by leveraging the exact decomposition proper…
Block-Based Double Decoders
Encoder-decoder models offer substantial inference-time savings over decoder-only models, but their pretraining objectives suffer from sparse supervision and dynamic sequence lengt…
Simply Stabilizing the Loop via Fully Looped Transformer
Scaling model performance typically requires increasing model size. Looped Transformer offers a compelling alternative by iteratively reusing the same Transformer blocks, trading a…
Robust Basis Spline Decoupling for the Compression of Transformer Models
Decoupling is a powerful modeling paradigm for representing multivariate functions as compositions of linear transformations and univariate nonlinear functions. A single-layer deco…
Disaggregated Serving for Hybrid SSM Models in vLLM
Hybrid architectures that interleave Mamba-style SSM layers with standard full-attention (FA) layers — such as NVIDIA Nemotron-H — are gaining traction as a way…