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Encoder

An encoder in machine learning is a neural network component that transforms input data (text, an image, audio, or code) into a compressed, structured representation, often called a latent representation…

Model Architecture

Hyena

Hyena is a sub-quadratic, attention-free neural sequence operator that replaces the self-attention operator of the Transformer with a recurrence of long, implicitly parameterized convolutions and…

Model Architecture

Layer normalization

Layer normalization is a technique for normalizing the activations of a neural network across the feature dimension of each individual sample, rather than across a batch of samples.

Model Architecture

Mamba 2

Mamba 2 is a state space model architecture introduced in the paper "Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality" by Tri Dao and Albert Gu

AI ModelsModel Architecture

Mamba-3

Mamba-3 is a sequence-modeling architecture in the state space model (SSM) family, introduced in March 2026 by researchers at Carnegie Mellon University and Princeton.

Model Architecture

RWKV

RWKV (pronounced "RwaKuv") is an open-source neural network architecture that combines the parallelizable training of Transformers with the constant-time

Machine LearningModel Architecture

Sparse attention

Sparse attention is a family of techniques that cut the computational and memory cost of the attention mechanism in transformer models by letting each token attend to only a subset of other tokens in a sequence

Machine LearningModel Architecture

SwiGLU

SwiGLU (Swish-Gated Linear Unit) is the activation function used inside the feed-forward sublayer of most modern transformer large language models, including LLaMA, PaLM, Mistral, Qwen, and DeepSeek.

Model ArchitectureNeural Networks

Transformers

A Transformer is a deep learning architecture, introduced by eight Google researchers in the 2017 paper "Attention Is All You Need", that uses attention as the sole mechanism for modeling relationships between…

Model ArchitectureNeural Networks

YaRN

YaRN (Yet another RoPE extensioN) is a compute-efficient method for extending the context window of large language models that use Rotary Position Embeddings (RoPE).

AI InferenceModel Architecture

xLSTM

xLSTM (Extended Long Short-Term Memory) is a recurrent neural network architecture introduced in May 2024 by Maximilian Beck, Korbinian Pöppel, Sepp Hochreiter, and collaborators at Johannes Kepler University…

Model ArchitectureNeural Networks