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 2751–2760 of 4891 papers

TitleStatusHype
FakeWatch: A Framework for Detecting Fake News to Ensure Credible Elections—0
Towards Unified Modeling for Positive and Negative Preferences in Sign-Aware Recommendation—0
Deep Learning for In-Orbit Cloud Segmentation and Classification in Hyperspectral Satellite Data—0
Sparse Bayesian Learning-Based Hierarchical Construction for 3D Radio Environment Maps Incorporating Channel Shadowing—0
Application of Distributed Arithmetic to Adaptive Filtering Algorithms: Trends, Challenges and Future—0
Efficient Language Model Architectures for Differentially Private Federated Learning—0
What Makes Quantization for Large Language Models Hard? An Empirical Study from the Lens of Perturbation—0
Monotone Individual Fairness—0
Decentralized and Lifelong-Adaptive Multi-Agent Collaborative LearningCode0
Efficient dual-scale generalized Radon-Fourier transform detector family for long time coherent integration—0
Show:102550
← PrevPage 276 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified