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 3101–3110 of 4891 papers

TitleStatusHype
Tropical Geometry Based Edge Detection Using Min-Plus and Max-Plus Algebra—0
Joint Delay-Phase Precoding Under True-Time Delay Constraints in Wideband Sub-THz Hybrid Massive MIMO Systems—0
Trusted Machine Learning Models Unlock Private Inference for Problems Currently Infeasible with Cryptography—0
Truthful Transaction Protocol for E-Commerce Networks Based on Double Auction—0
TSFormer: A Robust Framework for Efficient UHD Image Restoration—0
Tukey Depth Mechanisms for Practical Private Mean Estimation—0
Tumor-Centered Patching for Enhanced Medical Image Segmentation—0
TumorGen: Boundary-Aware Tumor-Mask Synthesis with Rectified Flow Matching—0
Tumor segmentation on whole slide images: training or prompting?—0
TurboAttention: Efficient Attention Approximation For High Throughputs LLMs—0
Show:102550
← PrevPage 311 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified