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 81–90 of 4891 papers

TitleStatusHype
A Technical Study into Small Reasoning Language Models—0
IKDiffuser: A Generative Inverse Kinematics Solver for Multi-arm Robots via Diffusion Model—0
VideoPDE: Unified Generative PDE Solving via Video Inpainting Diffusion Models—0
EBS-CFL: Efficient and Byzantine-robust Secure Clustered Federated LearningCode0
Structural feature enhanced transformer for fine-grained image recognition—0
Adaptive Multi-resolution Hash-Encoding Framework for INR-based Dental CBCT Reconstruction with Truncated FOV—0
Advances in LLMs with Focus on Reasoning, Adaptability, Efficiency and Ethics—0
Deep Fusion of Ultra-Low-Resolution Thermal Camera and Gyroscope Data for Lighting-Robust and Compute-Efficient Rotational Odometry—0
Directed Acyclic Graph Convolutional Networks—0
Data-driven approaches to inverse problems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified