Method, apparatus, device and storage medium for information processing
CN122122592APending Publication Date: 2026-05-29DOUYIN VISION CO LTD
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- DOUYIN VISION CO LTD
- Filing Date
- 2024-09-27
- Publication Date
- 2026-05-29
AI Technical Summary
Technical Problem
In existing neural network models, gradient vanishing and representation collapse caused by residual connections affect the model's processing efficiency and stability.
Method used
A learnable connection weight mechanism is introduced to optimize feature representation by dynamically adjusting the connection strength between network layers and combining depth and width connections.
Benefits of technology
It improves the processing efficiency and stability of the model, reduces representational collapse, enhances the network's representational power and gradient flow, and simplifies the network design process.
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Figure CN122122592A_ABST
Abstract
Embodiments of the present disclosure relate to a method, apparatus, device and storage medium for information processing. The method proposed herein includes: providing input information to a target model, the target model comprising a plurality of processing layers, the plurality of processing layers comprising at least an adjacent first processing layer and a second processing layer; determining, based on the input information, a first input feature associated with the first processing layer, the first input feature comprising a first set of feature components; applying a first set of weight parameters to the first set of feature components to determine an intermediate input feature; determining an intermediate output feature generated by the first processing layer based on the intermediate input feature; determining, based on the intermediate output feature and the first set of feature components, a second input feature associated with the second processing layer; and generating an output result of the target model based on at least the second input feature.
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