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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Published Paper Details:
Paper Title
META-LEARNING FRAMEWORKS FOR ADAPTIVE AUTOMATIC ADAPTATION
Authors
Suraj Sharma, Dr Madan Sharma
Keywords
Meta-learning, Adaptation, Automatic Learning, Few-shot Learning, Continual Learning
Abstract
In recent years, the demand for intelligent systems capable of rapidly and autonomously adapting to new tasks and environments has accelerated the development of meta-learning frameworks. Between 2024 and 2025, the field has seen substantial innovation, particularly in the design of meta-learning frameworks for adaptive automatic adaptation. These frameworks aim to enable machine learning models to generalize from prior experience and automatically adjust to unseen tasks with minimal data and computation. Unlike traditional learning paradigms that require extensive retraining, meta-learning provides a mechanism for "learning to learn," where the adaptation process itself is optimized during training.
IJCRT's Publication Details
Unique Identification Number - IJCRT2510698
Paper ID - 295521
Page Number(s) - f925-f933
Pubished in - Volume 13 | Issue 10 | October 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Suraj Sharma, Dr Madan Sharma, "META-LEARNING FRAMEWORKS FOR ADAPTIVE AUTOMATIC ADAPTATION", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 10, pp.f925-f933, October 2025, Available at :http://www.ijcrt.org/papers/IJCRT2510698.pdf
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Volume 14 | Issue 2
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February 2026
Volume 14 | Issue 2
Last Date :
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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