Inhibition Adaption on Pre-Trained Language Models

Information Science, Artificial Intelligence, Humanities and Others,
Pre-trained Language Models   Inhibition Adaption   Low Rank   Activation Functions   Text Classification   Question Answering Tasks  

InA: Inhibition Adaptation Method on Pre-trained Language Models Pre-trained Language Models (LMs) have achieved significant results in Natural Language Processing (NLP) tasks. However, traditional fine-tuning methods suffer from the problem of redundant parameters, which affects efficiency and effectiveness. To address this challenge, this paper p...

Heterogeneous Coexisting Attractors, Large-scale Amplitude Control, and Finite-time Synchronization of Central Cyclic Memristive Neural Networks

Physics, Electromagnetism, Information Science, Artificial Intelligence,
chaos   memristor   memristive neural networks   heterogeneous coexisting attractors   large-scale amplitude control   finite-time synchronization  

Heterogeneous Coexisting Attractors, Large-Scale Amplitude Control and Finite-Time Synchronization of Central Cyclic Memristive Neural Networks Academic Background Due to their memory and nonlinearity characteristics similar to brain synapses, memristors hold significant theoretical and practical importance in the study of chaotic dynamics in brain...

Adaptively Identify and Refine Ill-Posed Regions for Accurate Stereo Matching

Adaptively Identify and Refine Ill-Posed Regions for Accurate Stereo Matching

Information Science, Artificial Intelligence,
stereo matching   neural networks   feature refinement   ill-posed regions   image processing   error areas  

Adaptive Identification and Optimization of Ill-Posed Regions for Accurate Stereo Matching Research Background and Motivation With the rapid development of computer vision technology, stereo matching technology has played a crucial role in various fields such as robotics, aerospace, autonomous driving, and industrial manufacturing due to its high a...

Federated Learning Using Model Projection for Multi-Center Disease Diagnosis with Non-IID Data

Federated Learning Using Model Projection for Multi-Center Disease Diagnosis with Non-IID Data

Information Science, Artificial Intelligence, Medicine, Environmental and Public Health,
Federated Learning   Model Projection   Multi-Center Disease Diagnosis   Non-IID Data   Catastrophic Forgetting   Invalid Aggregation  

Federated Learning Using Model Projection for Multi-Center Disease Diagnosis Background Introduction With the rapid development of medical imaging technology, research on automated diagnostic methods has shown good performance on single-center datasets. However, these methods often find it difficult to generalize to data from other healthcare facil...

Adaptive Sampling Artificial-Actual Control for Non-Zero-Sum Games of Constrained Systems

Physics, Mechanics, Engineering, Electrical Engineering, Information Science, Computer Science, Automation, Artificial Intelligence,
adaptive dynamic programming   artificial-actual interaction   event-triggered mechanism   self-triggered mechanism  

Adaptive Sampling Artificial-Actual Control for Non-Zero-Sum Games of Constrained Systems Background In modern industrial and scientific research fields, the rapid development of intelligent technology and control systems makes traditional control methods difficult to meet the strict requirements of ensuring system stability and minimizing energy c...

Multi-Grained Visual Pivot-Guided Multi-Modal Neural Machine Translation with Text-Aware Cross-Modal Contrastive Disentangling

Multi-Grained Visual Pivot-Guided Multi-Modal Neural Machine Translation with Text-Aware Cross-Modal Contrastive Disentangling

Information Science, Automation, Artificial Intelligence, Humanities and Others,
multi-modal neural machine translation   cross-modal disentangling   semantic mismatch   multi-grained visual pivot  

Multi-Scale Vision-Centric Multi-Modal Neural Machine Translation: Text-Aware Cross-Modality Contrastive Decoupling Academic Background Multi-Modal Neural Machine Translation (MNMT) aims to incorporate language-independent visual information into text to enhance machine translation performance. However, due to the significant modal differences betw...