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 181–190 of 4891 papers

TitleStatusHype
CURVE: CLIP-Utilized Reinforcement Learning for Visual Image Enhancement via Simple Image Processing—0
AMBER: Adaptive Mesh Generation by Iterative Mesh Resolution PredictionCode0
LeMoRe: Learn More Details for Lightweight Semantic SegmentationCode0
THINK-Bench: Evaluating Thinking Efficiency and Chain-of-Thought Quality of Large Reasoning Models—0
Improving Out-of-Distribution Detection with Markov Logic Networks—0
Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs—0
NGPU-LM: GPU-Accelerated N-Gram Language Model for Context-Biasing in Greedy ASR Decoding—0
CPINN-ABPI: Physics-Informed Neural Networks for Accurate Power Estimation in MPSoCs—0
Target Localization with Coprime Multistatic MIMO Radar via Coupled Canonical Polyadic Decomposition Based on Joint Eigenvalue Decomposition—0
ZigzagPointMamba: Spatial-Semantic Mamba for Point Cloud Understanding—0
Show:102550
← PrevPage 19 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified