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Found 11 papers, 3 papers with code
Comparison of the effects of attention mechanism on translation tasks of different lengths of ambiguous words
This paper focuses on the performance of encoder decoder attention mechanism in word sense disambiguation task with different text length, trying to find out the influence of context marker on attention mechanism in word sense disambiguation task.
Ancestral Mamba: Enhancing Selective Discriminant Space Model with Online Visual Prototype Learning for Efficient and Robust Discriminant Approach
In the realm of computer graphics, the ability to learn continuously from non-stationary data streams while adapting to new visual patterns and mitigating catastrophic forgetting is of paramount importance.
Hierarchical Adaptive Expert for Multimodal Sentiment Analysis
HAEMSA employs a hierarchical structure of adaptive experts to capture both global and local modality representations, enabling more nuanced sentiment analysis.
STEAM-EEG: Spatiotemporal EEG Analysis with Markov Transfer Fields and Attentive CNNs
Electroencephalogram (EEG) signals play a pivotal role in biomedical research and clinical applications, including epilepsy diagnosis, sleep disorder analysis, and brain-computer interfaces.
GAF-FusionNet: Multimodal ECG Analysis via Gramian Angular Fields and Split Attention
Electrocardiogram (ECG) analysis plays a crucial role in diagnosing cardiovascular diseases, but accurate interpretation of these complex signals remains challenging.
Bio-Inspired Mamba: Temporal Locality and Bioplausible Learning in Selective State Space Models
This paper introduces Bio-Inspired Mamba (BIM), a novel online learning framework for selective state space models that integrates biological learning principles with the Mamba architecture.
Mamba-Spike: Enhancing the Mamba Architecture with a Spiking Front-End for Efficient Temporal Data Processing
This paper introduces Mamba-Spike, a novel neuromorphic architecture that integrates a spiking front-end with the Mamba backbone to achieve efficient and robust temporal data processing.
Zoom and Shift are All You Need
Feature alignment serves as the primary mechanism for fusing multimodal data.
MIPI 2024 Challenge on Few-shot RAW Image Denoising: Methods and Results
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems.
Alternative Telescopic Displacement: An Efficient Multimodal Alignment Method
In the realm of multimodal data integration, feature alignment plays a pivotal role.
Ranked #1 on
Arrhythmia Detection
on MIT-BIH Arrhythmia Database
TS-BERT: A fusion model for Pre-trainning Time Series-Text Representations
Use one of the news text and the stock data as the primary information source for the prediction task and the other as the auxiliary information source.
