State space models Mamba! Sequence modeling The goal of a sequence model is to map an input sequence, to an output sequence. We can map a continuous input signal x(t) to an output signal y(t) or a discrete input sequence to a discrete output sequence. Sequence modeling: models RNN CNN...
【Mamba详解】 - Mamba是一种新型的状态空间模型(State Space Model,SSM),它取得了和Transformer类似的性能,但可以处理更长的序列(例如100万token)。这是通过去除Attention机制中的“二次瓶颈”实现的。 - SS...
Mamba 的 hidden state 的维度比较高 如果一个输入 token 的 embedding 的维度是 d. Mamba 则会单独处理每一个维度, 而且每个维度的 hidden state 的 dimension 是 N. 也就是说, 总的维度 dN. 虽然 hidden state 的总大小还是和 RNN 一样不会随输入变长而变大 (Transformer 则完全不同, 详情可以看 zhihu...
Mamba与MoE架构强强联合,Mamba-MoE高效提升LLM计算效率和可扩展性 作为大型语言模型(LLM)基础架构的后起之秀,状态空间模型(State Space Models,SSMs)在序列数据建模领域中已取得了惊人的发展。其中Mamba模型改进了传统的SSM,其通过输入依赖的方式来调整SSM中的参数,允许模型自适应的根据输入数据选择性的传输或遗忘信息,...
Modeling sequences with structured state spaces, Responsibility: Albert Gu, Publication: [Stanford, California] : [Stanford University], 2023 [Thesis (330 pages)] [PDF] State Space Model for New-Generation Network Alternative to Transformers: A Survey, Xiao Wang, Shiao Wang, Yuhe Ding, Yuehang...
(ICLR 2023) H3: Hungry Hungry Hippos: Toward Language Modeling with State Space Models Paper CodeOther Useful SourcesMamba_State_Space_Model_Paper_ListAwesome State-Space Resources for MLAwesome-state-space-modelsVideo-of-HiPPOVideo-of-Mamba-and-S4-Explained...
State space models (SSM) with selection mechanisms and hardware-aware architectures, namely Mamba, have recently shown significant potential in long-sequence modeling. Since the complexity of transformers’ self-attention mechanism is quadratic with imag
Linearizing the system to its natural equilibrium point (i.e, minimum potential energy) yields a state space model, where the system inputs (u) are the actuators on the Mamba as described in the model and θ1X, θ2X and θ3X represent respectively the roll, pitch, and yaw axes state ...
exception explained below. Instead, kobjects are used to control access to a larger, domain-specific object. To this end, kobjects will be found embedded in other structures. If you are used to thinking of things in object-oriented terms, kobjects can be seen as a top-level, abstract class...
Selective State Spaces就是个扩维的Gated linear RNN,跟Linear Attention有着千丝万缕的联系。 你说State Spaces离散化我笑.jpg。首先data dependent的decay完全丧失了LTI的性质,非要叫State Space多多少少有点强行。其次个人完全不信离散化能有什么用。如果真有用,论文实现里也不至于把B的离散化直接简化成linear ...