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 2351–2360 of 4891 papers

TitleStatusHype
What Makes Quantization for Large Language Models Hard? An Empirical Study from the Lens of Perturbation—0
LinearAPT: An Adaptive Algorithm for the Fixed-Budget Thresholding Linear Bandit Problem—0
Fast Kernel Scene FlowCode1
CogView3: Finer and Faster Text-to-Image Generation via Relay DiffusionCode5
RFWave: Multi-band Rectified Flow for Audio Waveform ReconstructionCode2
Implementation of soft-constrained MPC for Tracking using its semi-banded problem structure—0
Enhanced Low-Dose CT Image Reconstruction by Domain and Task Shifting Gaussian Denoisers—0
Enhancing Price Prediction in Cryptocurrency Using Transformer Neural Network and Technical Indicators—0
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN—0
D4C Glove-train: Solving the RPM and Bongard-logo Problem by Circumscribing and Building Distribution for Concepts—0
Show:102550
← PrevPage 236 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified