SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

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Showing 461–470 of 4891 papers

TitleStatusHype
Efficient Temporal Extrapolation of Multimodal Large Language Models with Temporal Grounding BridgeCode1
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation LearningCode1
Federated Bayesian Optimization via Thompson SamplingCode1
FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated LearningCode1
DragLoRA: Online Optimization of LoRA Adapters for Drag-based Image Editing in Diffusion ModelCode1
DnS: Distill-and-Select for Efficient and Accurate Video Indexing and RetrievalCode1
Content-aware Token Sharing for Efficient Semantic Segmentation with Vision TransformersCode1
A new computationally efficient algorithm to solve Feature Selection for Functional Data Classification in high-dimensional spacesCode1
Ferret: Federated Full-Parameter Tuning at Scale for Large Language ModelsCode1
Geo-Sign: Hyperbolic Contrastive Regularisation for Geometrically Aware Sign Language TranslationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified