那么,如果将 LSTM 扩展到数十亿个参数,利用LLM技术打破LSTM的局限性,LSTM在语言建模方面还能走多远呢? 基于这个问题,本文作者提出xLSTM架构,与最先进的 Transformer 和状态空间模型(SSM)相比,在性能还是扩展方面都得到了显著的提升。LSTM迎来第二春? https://arxiv.org/pdf/2405.04517 背景介绍 长短期记忆网络(Long...
在这里,我们受到控制理论、储层(储备池)计算(reservoir computing)、深度学习和 RNN 的启发,提出了一种新的范式,称之为 “漩涡网络(Maelstrom Networks)范式”,结合了 RNN 的优点和前馈神经网络(FNN)的模式匹配能力。该范式将递归组件 - “Maelstrom” - 保持为未学习状态,并将学习任务转移至强大的前馈网络。这使...
状态空间模型(State Space Models,简称SSM)在控制理论中传统用于通过状态变量对动态系统建模。 Aaron R. VOELKER和Chris ELIASMITH提出了一个重要问题:大脑如何有效地表示时间信息。在他们2018年发表的论文《Improving Spiking Dynamical Networks: Accurate Delays, Higher-Order Synapses, and Time Cells》中,他们发现SSM...
LSTM一作新作xLSTM架构:大幅领先Transformer和状态空间模型(SSM) 这篇论文介绍了一种名为xLSTM(Extended Long Short-Term Memory)的新型递归神经网络架构,旨在解决传统LSTM(Long Short-Term Memory)网络的一些局限性,并提高其在语言建模等任务中的性能。 论文:xLSTM: Extended Long Short-Term Memory 链接:https://...
In recent advancements in medical image analysis, Convolutional Neural Networks (CNN) and Vision Transformers (ViT) have set significant benchmarks. While ... Z Wang,JQ Zheng,Y Zhang,... 被引量: 0发表: 2024年 RM-UNet: UNet-like Mamba with rotational SSM module for medical image segmentatio...
The SSM sensor interfacing RF Networks are designed to: Support Wireless Sensor Network with a minimum of components in the Bill of Material. To be very low power. To be very easy to implement. To have long range, several kilomteres for the SIGFOX sensor modules. ...
It does not discuss in detail the general operation of the protocols associated with developing interdomain multicast networks such as PIM-SM. This document contains the following sections: •Customer Business Objectives •Proposed Solution: URD Host Signalling •Implementation of Proposed ...
IGMP snooping SSM mapping is a Layer 2 SSM mapping feature used on IPv4 multicast networks. After static SSM mapping entries are configured on a Layer 2 device, the device can convert (*, G) information in IGMPv1 and IGMPv2 Report messages into (S, G) information to provide the SSM ser...
7.1 Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer, ICLR'17 7.2 GShard,2020.06, ICLR'21 7.3 Switch-C,2021.01 7.4 GLaM, 2021.12 7.6 Llama 7.7 GLA Transformer 2023.12 7.7 Transformer++ 8 Gemini 写在前面:本文记录一下研究者为提升模型在长序列任务建模能力所做的相关工...
MLD snooping SSM mapping is a Layer 2 SSM mapping feature used on IPv6 multicast networks. MLD snooping SSM mapping enables a Layer 2 device to convert (*, G) information in MLDv1 Report messages to (S, G) information based on static SSM mappings to provide the SSM services. Here, S...