{"total":41,"rows":[{"id":"2506.23075","title":"CSBrain: A Cross-scale Spatiotemporal Brain Foundation Model for EEG Decoding","created":"2025-06-29","cited_by_count":53,"area":null},{"id":"2503.04207","title":"Bridging the Vision-Brain Gap with an Uncertainty-Aware Blur Prior","created":"2025-03-06","cited_by_count":29,"area":null},{"id":"2205.10466","title":"A Survey on Physiological Signal Based Emotion Recognition","created":"2022-05-20","cited_by_count":12,"area":null},{"id":"2307.13463","title":"Unlocking the Emotional World of Visual Media: An Overview of the Science, Research, and Impact of Understanding Emotion","created":"2023-07-25","cited_by_count":12,"area":null},{"id":"2504.20069","title":"A Simple Review of EEG Foundation Models: Datasets, Advancements and Future Perspectives","created":"2025-04-24","cited_by_count":10,"area":null},{"id":"2405.00574","title":"EALD-MLLM: Emotion Analysis in Long-sequential and De-identity videos with Multi-modal Large Language Model","created":"2024-05-01","cited_by_count":8,"area":null},{"id":"2307.02819","title":"Trends in Machine Learning and Electroencephalogram (EEG): A Review for Undergraduate Researchers","created":"2023-07-06","cited_by_count":7,"area":null},{"id":"2404.09559","title":"Joint Contrastive Learning with Feature Alignment for Cross-Corpus EEG-based Emotion Recognition","created":"2024-04-15","cited_by_count":5,"area":null},{"id":"2309.15515","title":"GNN4EEG: A Benchmark and Toolkit for Electroencephalography Classification with Graph Neural Network","created":"2023-09-27","cited_by_count":4,"area":null},{"id":"2405.07260","title":"A Supervised Information Enhanced Multi-Granularity Contrastive Learning Framework for EEG Based Emotion Recognition","created":"2024-05-12","cited_by_count":2,"area":null},{"id":"2406.14014","title":"Feature Fusion Based on Mutual-Cross-Attention Mechanism for EEG Emotion Recognition","created":"2024-06-20","cited_by_count":2,"area":null},{"id":"2408.08979","title":"Electroencephalogram Emotion Recognition via AUC Maximization","created":"2024-08-16","cited_by_count":2,"area":null},{"id":"2408.10235","title":"Multi-Source EEG Emotion Recognition via Dynamic Contrastive Domain Adaptation","created":"2024-08-04","cited_by_count":2,"area":null},{"id":"2410.18103","title":"A Hybrid Graph Neural Network for Enhanced EEG-Based Depression Detection","created":"2024-10-08","cited_by_count":2,"area":null},{"id":"2504.03707","title":"Towards Practical Emotion Recognition: An Unsupervised Source-Free Approach for EEG Domain Adaptation","created":"2025-03-26","cited_by_count":2,"area":null},{"id":"2507.18026","title":"Emotion Recognition from Skeleton Data: A Comprehensive Survey","created":"2025-07-24","cited_by_count":2,"area":null},{"id":"2509.24302","title":"LEAF: Language-EEG Aligned Foundation Model for Brain-Computer Interfaces","created":"2025-09-29","cited_by_count":2,"area":null},{"id":"2511.12851","title":"NeuroLex: A Lightweight Domain Language Model for EEG Report Understanding and Generation","created":"2025-11-17","cited_by_count":2,"area":null},{"id":"2603.12722","title":"CognitionCapturerPro: Towards High-Fidelity Visual Decoding from EEG/MEG via Multi-modal Information and Asymmetric Alignment","created":"2026-03-13","cited_by_count":2,"area":null},{"id":"2305.05548","title":"CIT-EmotionNet: CNN Interactive Transformer Network for EEG Emotion Recognition","created":"2023-05-07","cited_by_count":1,"area":null},{"id":"2306.03112","title":"Synthesizing Affective Neurophysiological Signals Using Generative Models: A Review Paper","created":"2023-06-05","cited_by_count":1,"area":null},{"id":"2405.16701","title":"Detail-Enhanced Intra- and Inter-modal Interaction for Audio-Visual Emotion Recognition","created":"2024-05-26","cited_by_count":1,"area":null},{"id":"2504.09156","title":"LEL: Lipschitz Continuity Constrained Ensemble Learning for Efficient EEG-Based Intra-subject Emotion Recognition","created":"2025-04-12","cited_by_count":1,"area":null},{"id":"2507.14698","title":"Spatial-Temporal Transformer with Curriculum Learning for EEG-Based Emotion Recognition","created":"2025-07-19","cited_by_count":1,"area":null},{"id":"2304.07655","title":"EEGSN: Towards Efficient Low-latency Decoding of EEG with Graph Spiking Neural Networks","created":"2023-04-15","cited_by_count":0,"area":null},{"id":"2403.19014","title":"Thelxino\\\"e: Recognizing Human Emotions Using Pupillometry and Machine Learning","created":"2024-03-27","cited_by_count":0,"area":null},{"id":"2408.10328","title":"Decoding Human Emotions: Analyzing Multi-Channel EEG Data using LSTM Networks","created":"2024-08-19","cited_by_count":0,"area":null},{"id":"2409.07493","title":"Complex Emotion Recognition System using basic emotions via Facial Expression, EEG, and ECG Signals: a review","created":"2024-09-09","cited_by_count":0,"area":null},{"id":"2502.17172","title":"Teleology-Driven Affective Computing: A Causal Framework for Sustained Well-Being","created":"2025-02-24","cited_by_count":0,"area":null},{"id":"2503.18998","title":"FACE: Few-shot Adapter with Cross-view Fusion for Cross-subject EEG Emotion Recognition","created":"2025-03-24","cited_by_count":0,"area":null},{"id":"2507.10895","title":"Commuting Distance Regularization for Timescale-Dependent Label Inconsistency in EEG Emotion Recognition","created":"2025-07-15","cited_by_count":0,"area":null},{"id":"2508.05934","title":"ASLSL: Adaptive shared latent structure learning with incomplete multi-modal physiological data for multi-dimensional emotional feature selection","created":"2025-08-08","cited_by_count":0,"area":null},{"id":"2510.26304","title":"Exploring the correlation between the type of music and the emotions evoked: A study using subjective questionnaires and EEG","created":"2025-10-30","cited_by_count":0,"area":null},{"id":"2511.06782","title":"HEDN: A Hard-Easy Dual Network with Source Reliability Assessment for Cross-Subject EEG Emotion Recognition","created":"2025-11-10","cited_by_count":0,"area":null},{"id":"2511.08444","title":"One Model for All: Universal Pre-training for EEG based Emotion Recognition across Heterogeneous Datasets and Paradigms","created":"2025-11-11","cited_by_count":0,"area":null},{"id":"2603.04478","title":"Standing on the Shoulders of Giants: Rethinking EEG Foundation Model Pretraining via Multi-Teacher Distillation","created":"2026-03-04","cited_by_count":0,"area":null},{"id":"2603.26713","title":"Boundary-aware Prototype-driven Adversarial Alignment for Cross-Corpus EEG Emotion Recognition","created":"2026-03-18","cited_by_count":0,"area":null},{"id":"2604.25131","title":"Towards Unified Multi-task EEG Analysis with Low-Rank Adaptation","created":"2026-04-28","cited_by_count":0,"area":null},{"id":"2605.01235","title":"MindMelody: A Closed-Loop EEG-Driven System for Personalized Music Intervention","created":"2026-05-02","cited_by_count":0,"area":null},{"id":"2609.00846","title":"An Intelligent Decision Support System for Emotion Monitoring using Microscopic Fixational Dynamics","created":"2026-09-01","cited_by_count":0,"area":null},{"id":"2610.03618","title":"Video-Time Priors for EEG-fNIRS Emotion Regression on Familiar Videos","created":"2026-10-02","cited_by_count":0,"area":null}],"next_cursor":null}