Topic
Forgetting
About: Forgetting is a research topic. Over the lifetime, 7178 publications have been published within this topic receiving 255389 citations. The topic is also known as: forget & drawing a blank.
Papers published on a yearly basis
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Papers
Book•
3 Jul 2010
TL;DR: The Psychology of Learning and Motivation (PLM) series as mentioned in this paper is a collection of contributions in cognitive and experimental psychology, ranging from classical and instrumental conditioning to complex learning and problem solving.
Abstract: Psychology of Learning and Motivation publishes empirical and theoretical contributions in cognitive and experimental psychology, ranging from classical and instrumental conditioning to complex learning and problem solving. Each chapter thoughtfully integrates the writings of leading contributors, who present and discuss significant bodies of research relevant to their discipline. Volume 62 includes chapters on such varied topics as automatic logic and effortful beliefs, complex learning and development, bias detection and heuristics thinking, perceiving scale in real and virtual environments, using multidimensional encoding and retrieval contexts to enhance our understanding of source memory, causes and consequences of forgetting in thinking and remembering and people as contexts in conversation. * Volume 62 of the highly regarded Psychology of Learning and Motivation series* An essential reference for researchers and academics in cognitive science* Relevant to both applied concerns and basic research
5,855 citations
TL;DR: In this paper, the authors show that it is possible to train networks that can maintain expertise on tasks that they have not experienced for a long time by selectively slowing down learning on the weights important for those tasks.
Abstract: The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitable feature of connectionist models. We show that it is possible to overcome this limitation and train networks that can maintain expertise on tasks that they have not experienced for a long time. Our approach remembers old tasks by selectively slowing down learning on the weights important for those tasks. We demonstrate our approach is scalable and effective by solving a set of classification tasks based on a hand-written digit dataset and by learning several Atari 2600 games sequentially.
5,339 citations
Posted Content•
TL;DR: It is shown that it is possible to overcome the limitation of connectionist models and train networks that can maintain expertise on tasks that they have not experienced for a long time and selectively slowing down learning on the weights important for previous tasks.
Abstract: The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Neural networks are not, in general, capable of this and it has been widely thought that catastrophic forgetting is an inevitable feature of connectionist models. We show that it is possible to overcome this limitation and train networks that can maintain expertise on tasks which they have not experienced for a long time. Our approach remembers old tasks by selectively slowing down learning on the weights important for those tasks. We demonstrate our approach is scalable and effective by solving a set of classification tasks based on the MNIST hand written digit dataset and by learning several Atari 2600 games sequentially.
5,088 citations
TL;DR: For instance, the authors found that recall is more sensitive than familiarity to response speeding, division of attention, generation, semantic encoding, the effects of aging, and the amnestic effects of benzodiazepines, while familiarity is less sensitive to shifts in response criterion, fluency manipulations, forgetting over short retention intervals, and some perceptual manipulations.
3,919 citations
TL;DR: This chapter discusses the theoretical and empirical literature that addresses aging and discourse comprehension and a series of five studies guided by a particular working memory viewpoint regarding the formation of inferences during discourse processing are described.
Abstract: Publisher Summary This chapter discusses the theoretical and empirical literature that addresses aging and discourse comprehension. A series of five studies guided by a particular working memory viewpoint regarding the formation of inferences during discourse processing is described in the chapter. Compensatory strategies may be used with different degrees of likelihood across the life span largely as a function of efficiency with which inhibitory mechanisms function because these largely determine the facility with which memory can be searched. The consequences for discourse comprehension in particular may be profound because the establishment of a coherent representation of a message hinges on the timely retrieval of information necessary to establish coreference among certain critical ideas. Discourse comprehension is an ideal domain for assessing limited capacity frameworks because most models of discourse processing assume that multiple components, demanding substantially different levels of cognitive resources, are involved. For example, access to a lexical representation from either a visual array or an auditory message is virtually capacity free.
3,698 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2026 | 12 |
| 2025 | 477 |
| 2024 | 584 |
| 2023 | 1,295 |
| 2022 | 1,774 |
| 2021 | 604 |