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Working memory is a critical aspect of both human intelligence and artificial intelligence, serving as a workspace for the temporary storage and manipulation of information.
Language models are few-shot learners
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Age differences in short-term retention of rapidly changing information
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Working memory
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Individual Differences in Working Memory Capacity and What They Tell Us About Controlled Attention, General Fluid Intelligence, and Functions of the Prefrontal Cortex , 102–134
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The magical number 4 in short-term memory: A reconsideration of mental storage capacity
Cowan, N. 2001 · 2001
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Working Memory Capacity as Executive Attention
Engle, R. W. 2002 · 2002
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The Role of Prefrontal Cortex in Working-Memory Capacity, Executive Attention, and General Fluid Intelligence: An Individual-Differences Perspective
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Working Memory Span Tasks: A Methodological Review and User’s Guide
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Separating Cognitive Capacity from Knowledge: A New Hypothesis
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Improving Fluid Intelligence with Training on Working Memory
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An n-back task using vibrotactile stimulation with comparison to an auditory analogue
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Why Is Working Memory Related to Fluid Intelligence?
Salthouse, T. A.; and Pink, J. E. 2008 · 2008
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The turking test: Can language models understand instructions?
Efrat, A.; and Levy, O. 2020 · 2010
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The concurrent validity of the N-back task as a working memory measure
Jaeggi, S. M.; Buschkuehl, M.; Perrig, W. J.; and Meier, B. 2010 · 2010
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Control of interference during working memory updating
Szmalec, A.; Verbruggen, F.; Vandierendonck, A.; and Kemps, E. 2011 · 2011
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What Is Working Memory Capacity, and How Can We Measure It?
Wilhelm, O.; Hildebrandt, A.; and Oberauer, K. 2013 · 2013
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Improving Fluid Intelligence with Training on Working Memory: A Meta-Analysis
Au, J.; Sheehan, E.; Tsai, N.; Duncan, G. J.; Buschkuehl, M.; and Jaeggi, S. M. 2015 · 2015
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N-Back Related ERPs Depend on Stimulus Type, Task Structure, Pre-processing, and Lab Factors
Shalchy, M. A.; Pergher, V.; Pahor, A.; Van Hulle, M. M.; and Seitz, A. R. 2020 · 2020
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Meta-learning via language model in-context tuning
Chen, Y.; Zhong, R.; Zha, S.; Karypis, G.; and He, H. 2021 · 2021
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Large Language Models with Controllable Working Memory
Li, D.; Rawat, A. S.; Zaheer, M.; Wang, X.; Lukasik, M.; Veit, A.; Yu, F.; and Kumar, S. 2022 · 2022
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What Makes Good In-Context Examples for GPT-3?
Liu, J.; Shen, D.; Zhang, Y.; Dolan, B.; Carin, L.; and Chen, W. 2022 · 2022
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Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity
Lu, Y.; Bartolo, M.; Moore, A.; Riedel, S.; and Stenetorp, P. 2022 · 2022
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George Miller’s Magical Number of Immediate Memory in Retrospect: Observations on the Faltering Progression of Science
Cowan, N. 2015 · 2015
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Inability to suppress salient distractors predicts low visual working memory capacity
Gaspar, J. M.; Christie, G. J.; Prime, D. J.; Jolicœur, P.; and McDonald, J. J. 2016 · 2016
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What Limits Working Memory Capacity?
Oberauer, K.; Farrell, S.; Jarrold, C.; and Lewandowsky, S. 2016 · 2016
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Auditory Versus Visual Stimulus Effects on Cognitive Performance During the N-back Task
Amon, M. J.; and Bertenthal, B. I. 2018 · 2018
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Fluid Intelligence Is Related to Capacity in Memory as Well as Attention: Evidence from Middle Childhood and Adulthood
Cochrane, A.; Simmering, V.; and Green, C. S. 2019 · 2019
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Changes in Error Patterns during N-back Training Indicate Reliance on Subvocal Rehearsal
Chooi, W.-T.; and Logie, R. 2020 · 2020
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Working Memory and Intelligence , 504–527
Conway, A. R. A.; and Kovacs, K. 2020 · 2020
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Mechanisms of Distributed Working Memory in a Large-Scale Network of Macaque Neocortex
Mejías, J. F.; and Wang, X.-J. 2022 · 2022
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MetaICL: Learning to Learn In Context
Min, S.; Lewis, M.; Zettlemoyer, L.; and Hajishirzi, H. 2022 · 2022
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Reframing Instructional Prompts to GPTk’s Language
Mishra, S.; Khashabi, D.; Baral, C.; Choi, Y.; and Hajishirzi, H. 2022a · 2022
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Learning To Retrieve Prompts for In-Context Learning
Rubin, O.; Herzig, J.; and Berant, J. 2022 · 2022
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Sparks of artificial general intelligence: Early experiments with gpt-4
Bubeck, S.; Chandrasekaran, V.; Eldan, R.; Gehrke, J.; Horvitz, E.; Kamar, E.; Lee, P.; Lee, Y. T.; Li, Y.; Lundberg, S.; et al. 2023 · 2023
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Theory of mind may have spontaneously emerged in large language models
Kosinski, M. 2023 · 2023
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How do we know how smart AI systems are?
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