Naturalistic fMRI encoding must handle multimodal inputs, shifting fusion styles, and pronounced inter-subject variability. We introduce AFIRE (Agnostic Framework for Multimodal fMRI Response Encoding), an agnostic interface that standardizes time-aligned post-fusion tokens from varied encoders, and MIND, a plug-and-play Mixture-of-Experts decoder with a subject-aware dynamic gating. Trained end-to-end for whole-brain prediction, AFIRE decouples the decoder from upstream fusion, while MIND combines token-dependent Top-K sparse routing with a subject prior to personalize expert usage without sacrificing generality. Experiments across multiple multimodal backbones and subjects show consistent improvements over strong baselines, enhanced cross-subject generalization, and interpretable expert patterns that correlate with content type. The framework offers a simple attachment point for new encoders and datasets, enabling robust, plug-and-improve performance for naturalistic neuroimaging studies.
Rethinking Constraint Awareness for Efficient State Embedding of Neural Routing Solver
College of Computer Science and Software Engineering, Shenzhen University（深圳大学计算机科学与软件工程学院）；School of Automation and Intelligent Manufacturing, Southern University of Science and Technology（南方科技大学自动化与智能制造学院）；Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology, Southern University of Science and Technology（广东省全驱动系统控制理论与技术重点实验室，南方科技大学）；Pengcheng Laboratory（鹏城实验室）
A Physics-Inspired Classical Digital Twin of Cortical Dynamics: A Band-Stratified Metriplectic Port-Hamiltonian Neural Network Learned from Brain-Computer-Interface EEG
An Overlay Multicast Routing Method Based on Network Situational Awareness and Hierarchical Multi-Agent Reinforcement Learning
School of Information and Communication, Guilin University of Electronic Technology（桂林电子科技大学信息与通信学院）；School of Computer Science and Information Security, Guilin University of Electronic Technology（桂林电子科技大学计算机科学与信息安全学院）；Information Center, Guilin Medical University（桂林医学院信息中心）；School of Optoelectronic Engineering, Guilin University of Electronic Technology（桂林电子科技大学光电工程学院）
FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning
School of Life Sciences, IDG/McGovern Institute for Brain Research, Tsinghua University（生命科学学院，IDG/麦克格雷文脑科学研究院，清华大学）；Department of Psychological and Cognitive Sciences, Tsinghua University（心理学与认知科学系，清华大学）；School of Medicine, Shenzhen Campus of Sun Yat-Sen University（中山大学深圳校区医学学院）
ReFrame: Evidence-Guided Test-Time Safety Alignment in Multimodal Large Language Models
College of Computer Science and Technology, National University of Defense Technology（国防科技大学计算机学院）；State Key Laboratory of Complex & Critical Software Environment（复杂与关键软件环境国家重点实验室）；School of Computer Science, Wuhan University（武汉大学计算机学院）
MoxE: Mixture of xLSTM Experts with Entropy-Aware Routing for Efficient Language Modeling
FSM, University of Monastir（FSM，蒙斯塔尔大学）；CES Lab, ENIS, University of Sfax（CES实验室，ENIS，萨菲大学）；Department of Computer Science, College of Computer, Qassim University（计算机科学系，计算机学院，卡西姆大学）；University of Michigan-Flint（密歇根大学弗林特分校）
BrainCast: A Spatio-Temporal Forecasting Model for Whole-Brain fMRI Time Series Prediction
Institute of Advanced Technology, University of Science and Technology of China（科学技术大学先进技术研究院）；MoE Key Laboratory of Brain-Inspired Intelligence Perception and Cognition, University of Science and Technology of China（科学技术大学脑启发智能感知与认知教育部重点实验室）；School of Mathematics and Computer Sciences, Nanchang University（南昌大学数学与计算机科学学院）；School of Data Science, University of Virginia（弗吉尼亚大学数据科学学院）；Department of Biomedical Engineering, Tulane University（路易斯安那大学医学工程系）
