#attention mechanisms
26 papers · 1 filter
Multi-branch classification of diffuse cluster radio emission
Markus Bredberg, Emma Tolley
The paper investigates machine‑learning methods, specifically scattering‑transform encoders and squeeze‑excitation attention in multi‑branch neural networks, to improve detection o…
Face and Voice Cross-modal Association with Learning Convex Feature Embedding
Taewan Kim, Jiwoo Kang
The paper introduces a method that embeds face images and voice recordings into a shared convex feature space, using cross‑modal attention to reduce mismatches and improve verifica…
S-CEReBrO: Breaking the Memory Barrier in Continuous EEG Monitoring
Glenn Anta Bucagu, Thorir Mar Ingolfsson, Yawei Li +1
The paper introduces S-CEReBrO, a streaming Transformer architecture that uses a windowed alternating attention mechanism to keep memory usage constant during continuous EEG monito…
VCP-DCN: Beyond Visual Concealed Property via Depth Collaborative Network for Camouflaged Object Detection
Songsong Duan, Xi Yang, Nannan Wang
The paper proposes VCP-DCN, a depth collaborative network that aligns, interacts, and fuses RGB and depth features to improve camouflaged object detection in complex scenes.
THGFM: Dual-Branch Temporal Heterogeneous Graph Fusion Model
Yixin Peng, Diego Collarana, Er Jin +1
The paper introduces THGFM, a dual-branch graph transformer model that jointly handles structural heterogeneity and temporal dynamics in heterogeneous graphs using shared and speci…
A Compositional Theory of Causally Masked Transformers
Franz Nowak, Ryan Cotterell, Reda Boumasmoud
The paper develops an algebraic framework to characterize what decision problems finite‑precision, causally masked transformers can solve, linking attention mechanisms to memory re…