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 721–730 of 4891 papers

TitleStatusHype
Efficient Multi-agent Reinforcement Learning by PlanningCode1
Efficient Multi-scale Network with Learnable Discrete Wavelet Transform for Blind Motion DeblurringCode1
EfficientPose: Scalable single-person pose estimationCode1
Efficient Neural Network Robustness Certification with General Activation FunctionsCode1
Efficient Real-time Path Planning with Self-evolving Particle Swarm Optimization in Dynamic ScenariosCode1
Efficient RAW Image Deblurring with Adaptive Frequency ModulationCode1
Highly accurate and efficient deep learning paradigm for full-atom protein loop modeling with KarmaLoopCode1
Benchmarking the Robustness of Spatial-Temporal Models Against CorruptionsCode1
Birdie: Advancing State Space Models with Reward-Driven Objectives and CurriculaCode1
Hexatagging: Projective Dependency Parsing as TaggingCode1
Show:102550
← PrevPage 73 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified