Detection Transformer for Teeth Detection, Segmentation, and Numbering in Oral Rare Diseases: Focus on Data Augmentation and Inpainting Techniques
Paper • 2402.04408 • Published • 1
Abidoye Aanuoluwapo
Aanuoluwapo65
AI & ML interests
Computer vision and multimodal learning
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papers 1 day ago
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference
Paper • 2303.06182 • Published • 2
A Survey on Mixture of Experts
Paper • 2407.06204 • Published • 1
Multi-Head Mixture-of-Experts
Paper • 2404.15045 • Published • 61
CAMERA: Multi-Matrix Joint Compression for MoE Models via Micro-Expert Redundancy Analysis
Paper • 2508.02322 • Published • 1
Sub-MoE: Efficient Mixture-of-Expert LLMs Compression via Subspace Expert Merging
Paper • 2506.23266 • Published • 1
Shortcut-connected Expert Parallelism for Accelerating Mixture-of-Experts
Paper • 2404.05019 • Published • 2
Expert Race: A Flexible Routing Strategy for Scaling Diffusion Transformer with Mixture of Experts
Paper • 2503.16057 • Published • 15
Swin SMT: Global Sequential Modeling in 3D Medical Image Segmentation
Paper • 2407.07514 • Published • 1
MoE Parallel Folding: Heterogeneous Parallelism Mappings for Efficient Large-Scale MoE Model Training with Megatron Core
Paper • 2504.14960 • Published • 2
Uni-MoE: Scaling Unified Multimodal LLMs with Mixture of Experts
Paper • 2405.11273 • Published • 20
Capacity-Aware Inference: Mitigating the Straggler Effect in Mixture of Experts
Paper • 2503.05066 • Published • 5
GRIN: GRadient-INformed MoE
Paper • 2409.12136 • Published • 17
Scaling Laws for Native Multimodal Models Scaling Laws for Native Multimodal Models
Paper • 2504.07951 • Published • 31
A Hybrid Tensor-Expert-Data Parallelism Approach to Optimize Mixture-of-Experts Training
Paper • 2303.06318 • Published • 2
Chain-of-Experts: Unlocking the Communication Power of Mixture-of-Experts Models
Paper • 2506.18945 • Published • 42
Towards Greater Leverage: Scaling Laws for Efficient Mixture-of-Experts Language Models
Paper • 2507.17702 • Published • 7
Scalable Training of Mixture-of-Experts Models with Megatron Core
Paper • 2603.07685 • Published • 3
Towards a Multimodal Large Language Model with Pixel-Level Insight for Biomedicine
Paper • 2412.09278 • Published • 1
Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning
Paper • 2309.05444 • Published • 2