Web7 de nov. de 2024 · This paper proposes a systematic and unified benchmark, LRA, specifically focused on evaluating model quality under long-context scenarios. Our benchmark is a suite of tasks consisting of sequences ranging from $1K$ to $16K$ tokens, encompassing a wide range of data types and modalities such as text, natural, synthetic … WebOur benchmark is a suite of tasks consisting of sequences ranging from $1K$ to $16K$ tokens, encompassing a wide range of data types and modalities such as text, natural and synthetic images, and mathematical expressions requiring similarity, structural and visual-spatial reasoning. We systematically evaluate ten well established long-range ...

Long Range Arena: A Benchmark for Efficient Transformers

Web正好最近google的一篇文章LRA——《LONG RANGE ARENA: A BENCHMARK FOR EFFICIENT TRANSFORMERS》，提出了一个统一的标准比一比哪家的更厉害。文章从6 … WebRecurrent Neural Networks (RNNs) offer fast inference on long sequences but are hard to optimize and slow to train. Deep state-space models (SSMs) have recently been shown to perform remarkably well on long sequence modeling tasks, and have the added benefits of fast parallelizable training and RNN-like fast inference. However, while SSMs are … magnolia sectional couch

关于Performer的一些笔记 - 知乎

Web12 de nov. de 2024 · 2024-11-12. Comments 3. Google Research and DeepMind recently introduced Long-Range Arena (LRA), a benchmark for evaluating Transformer … WebWhile the focus of this paper is on efficient Transformer models, our benchmark is also model agnostic and can also serve as a benchmark for long-range sequence modeling. … Web14 de jan. de 2024 · On the Long Range Arena (LRA) benchmark for long-range sequence modeling, S4 sets a clear SotA on every task while being at least as computationally efficient as all competitors. It is the first sequence model to solve the Path-X task involving sequences of length 16384. magnolia seattle zip code