"parameter sharing" Papers

16 papers found

Basis Sharing: Cross-Layer Parameter Sharing for Large Language Model Compression

Jingcun Wang, Yu-Guang Chen, Ing-Chao Lin et al.

ICLR 2025arXiv:2410.03765
21
citations

Fast-in-Slow: A Dual-System VLA Model Unifying Fast Manipulation within Slow Reasoning

Hao Chen, Jiaming Liu, Chenyang Gu et al.

NEURIPS 2025
27
citations

Mitigate the Gap: Improving Cross-Modal Alignment in CLIP

Sedigheh Eslami, Gerard de Melo

ICLR 2025
15
citations

More Experts Than Galaxies: Conditionally-Overlapping Experts with Biologically-Inspired Fixed Routing

Sagi Shaier, Francisco Pereira, Katharina Kann et al.

ICLR 2025arXiv:2410.08003

MOSDT: Self-Distillation-Based Decision Transformer for Multi-Agent Offline Safe Reinforcement Learning

Yuchen Xia, Yunjian Xu

NEURIPS 2025

QMP: Q-switch Mixture of Policies for Multi-Task Behavior Sharing

Grace Zhang, Ayush Jain, Injune Hwang et al.

ICLR 2025oralarXiv:2302.00671
5
citations

Toward Efficient Multi-Agent Exploration With Trajectory Entropy Maximization

Tianxu Li, Kun Zhu

ICLR 2025
2
citations

UMoE: Unifying Attention and FFN with Shared Experts

Yuanhang Yang, Chaozheng Wang, Jing Li

NEURIPS 2025spotlightarXiv:2505.07260

VA-MoE: Variables-Adaptive Mixture of Experts for Incremental Weather Forecasting

Hao Chen, Tao Han, Song Guo et al.

ICCV 2025arXiv:2412.02503
3
citations

Dependency-aware Differentiable Neural Architecture Search

Buang Zhang, Xinle Wu, Hao Miao et al.

ECCV 2024
1
citations

FedLPS: Heterogeneous Federated Learning for Multiple Tasks with Local Parameter Sharing

Yongzhe Jia, Xuyun Zhang, Amin Beheshti et al.

AAAI 2024paperarXiv:2402.08578
11
citations

HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning

Shengchao Hu, Ziqing Fan, Li Shen et al.

ICML 2024arXiv:2405.18080
15
citations

Learning Causal Dynamics Models in Object-Oriented Environments

Zhongwei Yu, Jingqing Ruan, Dengpeng Xing

ICML 2024arXiv:2405.12615
4
citations

Multi-Task Dense Prediction via Mixture of Low-Rank Experts

Yuqi Yang, Peng-Tao Jiang, Qibin Hou et al.

CVPR 2024arXiv:2403.17749
60
citations

Not All Tasks Are Equally Difficult: Multi-Task Deep Reinforcement Learning with Dynamic Depth Routing

Jinmin He, Kai Li, Yifan Zang et al.

AAAI 2024paperarXiv:2312.14472
11
citations

Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching

Yichen Li, Wenchao Xu, Haozhao Wang et al.

ECCV 2024arXiv:2407.05005
29
citations