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 791–800 of 4891 papers

TitleStatusHype
AdaRank: Adaptive Rank Pruning for Enhanced Model MergingCode1
Finer-CAM: Spotting the Difference Reveals Finer Details for Visual ExplanationCode1
M^3amba: CLIP-driven Mamba Model for Multi-modal Remote Sensing ClassificationCode1
Fine-Grained Pillar Feature Encoding Via Spatio-Temporal Virtual Grid for 3D Object DetectionCode1
Simple random search provides a competitive approach to reinforcement learningCode1
Fine-tuning a Large Language Model for Automating Computational Fluid Dynamics SimulationsCode1
Prompt Tuned Embedding Classification for Multi-Label Industry Sector AllocationCode1
Speeding up and reducing memory usage for scientific machine learning via mixed precisionCode1
Implicit Regularization for Optimal Sparse RecoveryCode0
ArchComplete: Autoregressive 3D Architectural Design Generation with Hierarchical Diffusion-Based UpsamplingCode0
Show:102550
← PrevPage 80 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified