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 381–390 of 4891 papers

TitleStatusHype
Comparative Analysis of Demonstration Selection Algorithms for LLM In-Context LearningCode1
Complete Dictionary Learning via _p-norm MaximizationCode1
BUFFER: Balancing Accuracy, Efficiency, and Generalizability in Point Cloud RegistrationCode1
Fast Sequence Based Embedding with Diffusion GraphsCode1
Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative StudyCode1
Learning Hierarchical Image Segmentation For Recognition and By RecognitionCode1
Automated Lane Merging via Game Theory and Branch Model Predictive ControlCode1
Finer-CAM: Spotting the Difference Reveals Finer Details for Visual ExplanationCode1
Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PCCode1
AMD-Hummingbird: Towards an Efficient Text-to-Video ModelCode1
Show:102550
← PrevPage 39 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified