Cover Image

Uni-MoE-2.0-Omni: Scaling Language-Centric Omnimodal Large Model with Advanced MoE, Training and Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Yunxin, Chen, Xinyu, Jiang, Shenyuan, Shi, Haoyuan, Liu, Zhenyu, Zhang, Xuanyu, Deng, Nanhao, Xu, Zhenran, Ma, Yicheng, Zhang, Meishan, Hu, Baotian, Zhang, Min
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts
by: Li, Yunxin, et al.
Published: (2024)

UniMoE-Audio: Unified Speech and Music Generation with Dynamic-Capacity MoE
by: Liu, Zhenyu, et al.
Published: (2025)

MSVBench: Towards Human-Level Evaluation of Multi-Shot Video Generation
by: Shi, Haoyuan, et al.
Published: (2026)

OmniMoE: An Efficient MoE by Orchestrating Atomic Experts at Scale
by: Shi, Jingze, et al.
Published: (2026)

Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs
by: Tang, Yehui, et al.
Published: (2025)

Grove MoE: Towards Efficient and Superior MoE LLMs with Adjugate Experts
by: Wu, Haoyuan, et al.
Published: (2025)

LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing
by: Nie, Xiaonan, et al.
Published: (2024)

EPS-MoE: Expert Pipeline Scheduler for Cost-Efficient MoE Inference
by: Qian, Yulei, et al.
Published: (2024)

Training Report of TeleChat3-MoE
by: Liu, Xinzhang, et al.
Published: (2025)

SP-MoE: Speculative Decoding and Prefetching for Accelerating MoE-based Model Inference
by: Chen, Liangkun, et al.
Published: (2025)

GRACE-MoE: Grouping and Replication with Locality-Aware Routing for Efficient Distributed MoE Inference
by: Han, Yu, et al.
Published: (2025)

MoE Parallel Folding: Heterogeneous Parallelism Mappings for Efficient Large-Scale MoE Model Training with Megatron Core
by: Liu, Dennis, et al.
Published: (2025)

AquilaMoE: Efficient Training for MoE Models with Scale-Up and Scale-Out Strategies
by: Zhang, Bo-Wen, et al.
Published: (2024)

LLaDA-MoE: A Sparse MoE Diffusion Language Model
by: Zhu, Fengqi, et al.
Published: (2025)

MiM-DiT: MoE in MoE with Diffusion Transformers for All-in-One Image Restoration
by: Kong, Lingshun, et al.
Published: (2026)

FEPLB: Exploiting Copy Engines for Nearly Free MoE Load Balancing in Distributed Training
by: Qi, Shuyao, et al.
Published: (2026)

MoE-Compression: How the Compression Error of Experts Affects the Inference Accuracy of MoE Model?
by: Ma, Songkai, et al.
Published: (2025)

Staleness-Centric Optimizations for Parallel Diffusion MoE Inference
by: Luo, Jiajun, et al.
Published: (2024)

UniEP: Unified Expert-Parallel MoE MegaKernel for LLM Training
by: Zheng, Size, et al.
Published: (2026)

MoEBlaze: Breaking the Memory Wall for Efficient MoE Training on Modern GPUs
by: Zhang, Jiyuan, et al.
Published: (2026)

Advancing Expert Specialization for Better MoE
by: Guo, Hongcan, et al.
Published: (2025)

MoE-Prism: Disentangling Monolithic Experts for Elastic MoE Services via Model-System Co-Designs
by: Xia, Xinfeng, et al.
Published: (2025)

MoE-Sieve: Routing-Guided LoRA for Efficient MoE Fine-Tuning
by: Manzoni, Andrea
Published: (2026)

OD-MoE: On-Demand Expert Loading for Cacheless Edge-Distributed MoE Inference
by: Wang, Liujianfu, et al.
Published: (2025)

HierMoE: Accelerating MoE Training with Hierarchical Token Deduplication and Expert Swap
by: Lin, Wenxiang, et al.
Published: (2025)

MoE-Lightning: High-Throughput MoE Inference on Memory-constrained GPUs
by: Cao, Shiyi, et al.
Published: (2024)

MoE-Hub: Taming Software Complexity for Seamless MoE Overlap with Hardware-Accelerated Communication on Multi-GPU Systems
by: Zhou, Zhuoshan, et al.
Published: (2026)

Accelerating Distributed MoE Training and Inference with Lina
by: Li, Jiamin, et al.
Published: (2022)

Sparse Checkpointing for Fast and Reliable MoE Training
by: Gandhi, Swapnil, et al.
Published: (2024)

GRIN: GRadient-INformed MoE
by: Liu, Liyuan, et al.
Published: (2024)

Dense2MoE: Restructuring Diffusion Transformer to MoE for Efficient Text-to-Image Generation
by: Zheng, Youwei, et al.
Published: (2025)

BIG-MoE: Bypass Isolated Gating MoE for Generalized Multimodal Face Anti-Spoofing
by: Ma, Yingjie, et al.
Published: (2024)

Cognitive Visual-Language Mapper: Advancing Multimodal Comprehension with Enhanced Visual Knowledge Alignment
by: Li, Yunxin, et al.
Published: (2024)

GazeFormer-MoE: Context-Aware Gaze Estimation via CLIP and MoE Transformer
by: Zhao, Xinyuan, et al.
Published: (2026)

Stabilizing MoE Reinforcement Learning by Aligning Training and Inference Routers
by: Ma, Wenhan, et al.
Published: (2025)

Routing Matters in MoE: Scaling Diffusion Transformers with Explicit Routing Guidance
by: Wei, Yujie, et al.
Published: (2025)

Symbiotic-MoE: Unlocking the Synergy between Generation and Understanding
by: Liu, Xiangyue, et al.
Published: (2026)

WindowsWorld: A Process-Centric Benchmark of Autonomous GUI Agents in Professional Cross-Application Environments
by: Li, Jinchao, et al.
Published: (2026)

LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation
by: Shu, Fangxun, et al.
Published: (2024)

MoE-Gen: High-Throughput MoE Inference on a Single GPU with Module-Based Batching
by: Xu, Tairan, et al.
Published: (2025)