我要威胁
发表于 2025-3-30 08:27:44
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fastness
发表于 2025-3-30 12:37:18
Meta-pruning: Learning to Prune on Few-Shot Learningtting risks, we propose a new meta-learning method termed Meta-Pruning, which diverges from traditional pruning methods by treating pruning as a learnable task and training the model to discern and select beneficial network connections for new tasks. We propose to set the corresponding learning rate
宴会
发表于 2025-3-30 19:10:55
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syncope
发表于 2025-3-30 22:57:04
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记忆法
发表于 2025-3-31 01:40:38
DSCVSR: A Lightweight Video Super-Resolution for Arbitrary Magnificationdeep learning introduces a large number of parameters, which can result in a large resource overhead, the model cannot be deployed on edge devices. Therefore, in this paper, we design a lightweight video super-resolution model, named Depthwise Separable Convolutional Video Super-Resolution (DSCVSR),
Spinous-Process
发表于 2025-3-31 07:43:52
Programming Knowledge Tracing with Context and Structure Integrationassignment tasks. Previous approaches typically focused on either the structural or contextual representation of code to model PKT. However, relying solely on one type of these code representations may fail to capture the subtle differences in the student-submitted code, leading to inferior tracing
玷污
发表于 2025-3-31 11:17:19
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转换
发表于 2025-3-31 15:29:43
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相容
发表于 2025-3-31 17:54:52
User Story Classification with Machine Learning and LLMspted to classify different aspects of user stories in the past. However, classifying the . class has been largely overlooked. To this aim, we present three pipelines. The first two pipelines rely on standard machine learning methods. They differ in how they represent features, i.e. bag-of-word vs. e
裁决
发表于 2025-4-1 01:37:39
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