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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 371–380 of 4891 papers

TitleStatusHype
Improving Temporal Link Prediction via Temporal Walk Matrix ProjectionCode1
TPP-LLM: Modeling Temporal Point Processes by Efficiently Fine-Tuning Large Language ModelsCode1
2D-TPE: Two-Dimensional Positional Encoding Enhances Table Understanding for Large Language ModelsCode1
HDFlow: Enhancing LLM Complex Problem-Solving with Hybrid Thinking and Dynamic WorkflowsCode1
TiM4Rec: An Efficient Sequential Recommendation Model Based on Time-Aware Structured State Space Duality ModelCode1
AIM 2024 Challenge on UHD Blind Photo Quality AssessmentCode1
DecoupleNet: A Lightweight Backbone Network With Efficient Feature Decoupling for Remote Sensing Visual TasksCode1
MambaClinix: Hierarchical Gated Convolution and Mamba-Based U-Net for Enhanced 3D Medical Image SegmentationCode1
Ferret: Federated Full-Parameter Tuning at Scale for Large Language ModelsCode1
M3-Jepa: Multimodal Alignment via Multi-directional MoE based on the JEPA frameworkCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified