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 1771–1780 of 4891 papers

TitleStatusHype
InfraLib: Enabling Reinforcement Learning and Decision-Making for Large-Scale Infrastructure Management—0
Exact first passage time distribution for second-order reactions in chemical networks—0
Efficient Image Compression Using Advanced State Space Models—0
Deep Adaptive Interest Network: Personalized Recommendation with Context-Aware Learning—0
Relative-Translation Invariant Wasserstein Distance—0
Configurable Foundation Models: Building LLMs from a Modular Perspective—0
Fast, High-Quality and Parameter-Efficient Articulatory Synthesis using Differentiable DSP—0
TASL-Net: Tri-Attention Selective Learning Network for Intelligent Diagnosis of Bimodal Ultrasound Video—0
Efficiently Expanding Receptive Fields: Local Split Attention and Parallel Aggregation for Enhanced Large-scale Point Cloud Semantic Segmentation—0
SA-MLP: A Low-Power Multiplication-Free Deep Network for 3D Point Cloud Classification in Resource-Constrained EnvironmentsCode0
Show:102550
← PrevPage 178 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified