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NIAID Data Ecosystem2026-05-01 收录

Transformer模型

注意力机制

数据链接：

https://data.mendeley.com/datasets/rb2smsh8xv 数据链接链接失效反馈

官方服务：

资源简介：

The dataset for the paper "Interpretation of the Transformer and Improvement of the Extractor" and the paper "Attention Is Not All You Need Anymore".

创建时间：

2023-11-23

synthseq/flipflop

语言模型

注意力机制

该数据集用于Flip-Flop Language Modeling任务，旨在正确执行1位寄存器的顺序操作。尽管Transformer架构似乎适合此操作，但它会偶尔出现外推错误（称为注意力故障）。一个开放的挑战是如何在不依赖长尾数据或递归架构的情况下修复这些错误。数据集包含训练集、验证集、密集验证集和稀疏验证集，分别来自不同的FFL配置。

Hugging Face2023-10-19 更新240

Transformer_Reinforcement_Learning

强化学习

Transformer模型

It may be deleted at any time.

kaggle2024-04-12 更新80

The Impact of Hearing Impairment on Neural and Behavioural Signatures of Attentional Filtering

认知神经科学

注意力机制

This is a dataset being published as part of the SNSF Ambizione project: Exploiting the potential of neural attentional control to overcome hearing impairment (https://data.snf.ch/grants/grant/20186

Zenodo2026-04-23 更新30

Universal Approximation and Optimization Theory for Multi-Head Self-Attention: Theoretical Foundations and Scaling Laws

机器学习理论

Transformer模型

We have established comprehensive theoretical foundations for understanding multi-head self-attention mechanisms through universal approximation theory and convex optimization. Our analysis reveals th

Figshare2025-07-28 更新90

Testing the Attentional Dwelling Hypothesis of Attentional Capture

感知与认知心理学

注意力机制

Data sets for the two experiments published in "Testing the Attentional Dwelling Hypothesis of Attentional Capture" by Lamy D., Darnell. M., Levy A. and Bublil, C. in `journal Of Cognition (2018)

DataCite Commons2020-08-28 更新70

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