{"total":27,"rows":[{"id":"2210.14793","title":"M$^3$ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design","created":"2022-10-26","cited_by_count":98,"area":"moe"},{"id":"2206.04674","title":"Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs","created":"2022-06-09","cited_by_count":58,"area":"moe"},{"id":"2307.15324","title":"TaskExpert: Dynamically Assembling Multi-Task Representations with Memorial Mixture-of-Experts","created":"2023-07-28","cited_by_count":45,"area":"moe"},{"id":"2510.08396","title":"FlyLoRA: Boosting Task Decoupling and Parameter Efficiency via Implicit Rank-Wise Mixture-of-Experts","created":"2025-10-09","cited_by_count":35,"area":"moe"},{"id":"2410.14972","title":"MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning","created":"2024-10-19","cited_by_count":23,"area":"moe"},{"id":"2503.08564","title":"MoE-Loco: Mixture of Experts for Multitask Locomotion","created":"2025-03-11","cited_by_count":23,"area":"moe"},{"id":"2212.08066","title":"Mod-Squad: Designing Mixture of Experts As Modular Multi-Task Learners","created":"2022-12-15","cited_by_count":15,"area":"moe"},{"id":"2505.24378","title":"Mastering Massive Multi-Task Reinforcement Learning via Mixture-of-Expert Decision Transformer","created":"2025-05-30","cited_by_count":15,"area":"moe"},{"id":"2410.02475","title":"Efficient Residual Learning with Mixture-of-Experts for Universal Dexterous Grasping","created":"2024-10-03","cited_by_count":10,"area":"moe"},{"id":"2601.02967","title":"MoE Adapter for Large Audio Language Models: Sparsity, Disentanglement, and Gradient-Conflict-Free","created":"2026-01-06","cited_by_count":5,"area":"moe"},{"id":"2309.00380","title":"Learning multi-modal generative models with permutation-invariant encoders and tighter variational objectives","created":"2023-09-01","cited_by_count":4,"area":"moe"},{"id":"2603.12378","title":"NeuroLoRA: Context-Aware Neuromodulation for Parameter-Efficient Multi-Task Adaptation","created":"2026-03-12","cited_by_count":4,"area":"moe"},{"id":"2510.24055","title":"Language-Conditioned Representations and Mixture-of-Experts Policy for Robust Multi-Task Robotic Manipulation","created":"2025-10-28","cited_by_count":2,"area":"moe"},{"id":"2603.03967","title":"UniRain: Unified Image Deraining with RAG-based Dataset Distillation and Multi-objective Reweighted Optimization","created":"2026-03-04","cited_by_count":2,"area":"moe"},{"id":"2603.29765","title":"Training-Free Dynamic Upcycling of Expert Language Models","created":"2026-03-31","cited_by_count":1,"area":"moe"},{"id":"2609.03150","title":"Routing Is Not Enough: Diagnosing Intra-Adapter Subspace Contention in MoE+LoRA Fine-Tuning","created":"2026-09-02","cited_by_count":1,"area":"moe"},{"id":"2501.06884","title":"Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learning","created":"2025-01-12","cited_by_count":0,"area":"moe"},{"id":"2512.02224","title":"Towards Unified Video Quality Assessment","created":"2025-12-01","cited_by_count":0,"area":"moe"},{"id":"2512.20291","title":"Mixture-of-Experts with Gradient Conflict-Driven Subspace Topology Pruning for Emergent Modularity","created":"2025-12-23","cited_by_count":0,"area":"moe"},{"id":"2604.00074","title":"PASM: Population Adaptive Symbolic Mixture-of-Experts Model for Cross-location Hurricane Evacuation Decision Prediction","created":"2026-03-31","cited_by_count":0,"area":"moe"},{"id":"2604.01762","title":"FourierMoE: Fourier Mixture-of-Experts Adaptation of Large Language Models","created":"2026-04-02","cited_by_count":0,"area":"moe"},{"id":"2605.15179","title":"Eradicating Negative Transfer in Multi-Physics Foundation Models via Sparse Mixture-of-Experts Routing","created":"2026-05-14","cited_by_count":0,"area":"moe"},{"id":"2606.31201","title":"ExPLoRe: Expert Patch-Level Loss Routing for Multi-Objective Masked Image Modeling","created":"2026-06-30","cited_by_count":0,"area":"moe"},{"id":"2607.00293","title":"Rosetta: Composable Native Multimodal Pretraining","created":"2026-07-01","cited_by_count":0,"area":"moe"},{"id":"2607.14334","title":"MixCompress: Mixture of Experts for Variable Rate Learned Image Compression","created":"2026-07-15","cited_by_count":0,"area":"moe"},{"id":"2608.24763","title":"MoTE: Mixture of Task Experts for Multi-Task Video Understanding","created":"2026-08-25","cited_by_count":0,"area":"moe"},{"id":"2609.39137","title":"ID Balancing: Stable Training of Extremely Sparse MoE via PID-Based Load Control","created":"2026-09-30","cited_by_count":0,"area":"moe"}],"next_cursor":null}