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This paper explores Memory-Augmented Neural Networks (MANNs), delving into how they blend human-like memory processes into AI.
The magical number seven, plus or minus two: Some limits on our capacity for processing information
George A Miller · 1956
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Human memory: A proposed system and its control processes
Richard C Atkinson and Richard M Shiffrin · 1968
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Correlation matrix memories
Teuvo Kohonen · 1972
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Working memory
Alan D. Baddeley and Graham Hitch · 1974
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Neural networks and physical systems with emergent collective computational abilities
J J Hopfield · 1982
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Connectionist models of recognition memory: constraints imposed by learning and forgetting functions
Roger Ratcliff · 1990
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber · 1997
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Working memory, thought, and action
Alan Baddeley · 2007
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What are the differences between long-term, short-term, and working memory?
Nelson Cowan · 2008
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Primed to sleep: The dynamics of synaptic plasticity across sleep-wake cycles
Frank and Benington · 2013
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Neural turing machines, 2014
Alex Graves, Greg Wayne, and Ivo Danihelka · 2014
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Introduction to psychology
Charles Stangor and Jennifer Walinga · 2014
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Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension, 2019
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer · 2019
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Transformers are rnns: Fast autoregressive transformers with linear attention, 2020
Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas, and François Fleuret · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela · 2021
Knn-diffusion: Image generation via large-scale retrieval, 2022
Shelly Sheynin, Oron Ashual, Adam Polyak, Uriel Singer, Oran Gafni, Eliya Nachmani, and Yaniv Taigman · 2022
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Retrieval-augmented diffusion models
Andreas Blattmann, Robin Rombach, Kaan Oktay, Jonas Müller, and Björn Ommer · 2022
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Retrieval augmented visual question answering with outside knowledge
Weizhe Lin and Bill Byrne · 2022
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Cm3: A causal masked multimodal model of the internet, 2022
Armen Aghajanyan, Bernie Huang, Candace Ross, Vladimir Karpukhin, Hu Xu, Naman Goyal, Dmytro Okhonko, Mandar Joshi, Gargi Ghosh, Mike Lewis, and Luke Zettlemoyer · 2022
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Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning
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One question answering model for many languages with cross-lingual dense passage retrieval
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Jurassic-1: Technical details and evaluation
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Semi-parametric neural image synthesis, 2022
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Task-aware retrieval with instructions, 2022
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Attention is all you need, 2023
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Haotian Liu, Kilho Son, Jianwei Yang, Ce Liu, Jianfeng Gao, Yong Jae Lee, and Chunyuan Li · 2023
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Reveal: Retrieval-augmented visual-language pre-training with multi-source multimodal knowledge memory
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