Differential Attention

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10 papers3 papers in the last four weeks, with none the four weeks before. 0.0% of all new papers.

AFA-Net: A Differential Attention Approach for Auditory Attention Detection
Sep 25, 2026Philip H. Lee, Shreeram Suresh Chandra, Karan Thakkar +1Differential Attention EEG Decoding
Independent Researcher, USA · Center for Language and Speech Processing (CLSP), Johns Hopkins University, USA · Laboratory for Computational Audio Perception (LCAP), Johns Hopkins University, USA +1
Differential Attention Unlocks Complementary EEG and Speech Fusion for Emotion Recognition
Sep 25, 2026Philip H. Lee, Shreeram Suresh Chandra, John H. L. HansenEEG Artifact Removal Differential Attention
Independent Researcher, USA · Center for Language and Speech Processing (CLSP), Johns Hopkins University, Baltimore, MD, USA · Center for Robust Speech Systems (CRSS), University of Texas at Dallas, Richardson, TX, USA
M3D-Net: Hierarchical Coordination of Spatial Context, Feature Reuse, and Differential Attention for Mammography Classification
Sep 23, 2026Zheng Yu, Xinhang Li, Jiabao Gao +2Multi-Scale Feature Fusion Medical Image Classification
Shenzhen Loop Area Institute, Shenzhen, China · The Chinese University of Hong Kong, Shenzhen, China · Shenzhen Research Institute of Big Data, Shenzhen, China
HADT: A Heterogeneous Multi-Agent Differential Transformer for Autonomous Earth Observation Satellite Cluster
May 29, 2026Mohamad A. Hady, Muhammad Anwar Masum, Siyi Hu +3Transformer Remote Sensing
School of Computer Science and Information Technology, Adelaide University, Adelaide, 5095, SA, Australia. · School of Electrical Engineering, Computing and Mathematical Sciences (EECMS), Curtin University, Kent St, Bentley, 6102, WA, Australia. · Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland.
Falcon-X: A Time Series Foundation Model for Heterogeneous Multivariate Modeling
May 26, 2026Yiding Liu, Yifan Hu, Hongjie Xia +5Multivariate Time Series Forecasting Zero-Shot Time Series Forecasting
Attention Dispersion in Dynamic Graph Transformers: Diagnosis and a Transferable Fix
May 15, 2026Jinhao Zhang, Kangfei Zhao, Qiuhao Zeng +1Distribution Shift Robustness Temporal GNNs
Beijing Institute of Technology · University of Toronto · Hong Kong Baptist University
Relational graph-driven differential denoising and diffusion attention fusion for multimodal conversation emotion recognition
Mar 22, 2026Ying Liu, Yuntao Shou, Wei Ai +2Differential Attention Emotion Recognition in Conversations
College of Computer and Mathematics, Central South University of Forestry and Technology, 410004, Hunan, Changsha China · Department of Computer Science, State University of New York, New Paltz, New York, 12561, USA
GraphDiffMed: Knowledge-Constrained Differential Attention with Pharmacological Graph Priors for Medication Recommendation
Mar 21, 2026Krati Saxena, Tomohiro ShibataMedication Recommendation Differential Attention
Kyushu Institute of Technology, Kitakyushu, Fukuoka, Japan
SaFeR: Safety-Critical Scenario Generation for Autonomous Driving Test via Feasibility-Constrained Token Resampling
Mar 4, 2026Jinlong Cui, Fenghua Liang, Guo Yang +2Differential Attention Autonomous Driving Scenario Generation
the School of Traffic and Transportation, Harbin Institute of Technology, Harbin, China and Chongqing Research Institute of HIT, Chongqing, China · the Chongqing Changan Automobile Company Ltd, Chongqing, China
GRAD-Former: Gated Robust Attention-based Differential Transformer for Change Detection
Mar 1, 2026Durgesh Ameta, Ujjwal Mishra, Praful Hambarde +1Differential Attention Remote Sensing Change Detection
School of Computing, IIIT Una HP-177209, India · Center of Artificial Intelligence and Robotics (CAIR), IIT Mandi, Mandi, HP 175005, India

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AFA-Net: A Differential Attention Approach for Auditory Attention Detection

Philip H. Lee, Shreeram Suresh Chandra, Karan Thakkar, John H. L. Hansen

Independent Researcher, USA · Center for Language and Speech Processing (CLSP), Johns Hopkins University, USA · Laboratory for Computational Audio Perception (LCAP), Johns Hopkins University, USA+1

Differential Attention EEG Decoding

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Auditory Attention Detection (AAD) utilizes electroencephalographic (EEG) signals to identify a target speaker in a multi-speaker environment. Despite considerable progress, existing deep learning architectures often lack explicit mechanisms for handling noisy EEG data. To address this limitation, we propose Auditory Focus Attention Networks (AFA-Net), a machine learning framework that replaces vanilla attention with a simple yet flexible differential attention mechanism to help focus on task-relevant neural activity. AFA-Net achieves an upward accuracy of 96.8% at the 2s decision window, while using substantially fewer parameters than most existing methods. To the best of our knowledge, AFA-Net is among the first frameworks to explicitly try to combat EEG noise to improve AAD.