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 1526–1550 of 4891 papers

TitleStatusHype
An Enhancement of Jiang, Z., et al.s Compression-Based Classification Algorithm Applied to News Article Categorization—0
Leveraging Small LLMs for Argument Mining in Education: Argument Component Identification, Classification, and Assessment—0
Moshi Moshi? A Model Selection Hijacking Adversarial Attack—0
QUAD-LLM-MLTC: Large Language Models Ensemble Learning for Healthcare Text Multi-Label Classification—0
Fundamental Survey on Neuromorphic Based Audio Classification—0
Triply Laplacian Scale Mixture Modeling for Seismic Data Noise SuppressionCode0
InstaSHAP: Interpretable Additive Models Explain Shapley Values Instantly—0
Investigating Non-Transitivity in LLM-as-a-Judge—0
SegRet: An Efficient Design for Semantic Segmentation with Retentive NetworkCode0
EfficientPose 6D: Scalable and Efficient 6D Object Pose Estimation—0
Backpropagation-free Spiking Neural Networks with the Forward-Forward Algorithm—0
Risk-Sensitive Security-Constrained Economic Dispatch: Pricing and Algorithm Design—0
ThinkGuard: Deliberative Slow Thinking Leads to Cautious GuardrailsCode0
CondensNet: Enabling stable long-term climate simulations via hybrid deep learning models with adaptive physical constraints—0
Activation-wise Propagation: A Universal Strategy to Break Timestep Constraints in Spiking Neural Networks for 3D Data Processing—0
DSMoE: Matrix-Partitioned Experts with Dynamic Routing for Computation-Efficient Dense LLMs—0
Revisiting Privacy, Utility, and Efficiency Trade-offs when Fine-Tuning Large Language Models—0
Minimal Ranks, Maximum Confidence: Parameter-efficient Uncertainty Quantification for LoRACode0
iMOVE: Instance-Motion-Aware Video Understanding—0
Symmetric Rank-One Quasi-Newton Methods for Deep Learning Using Cubic Regularization—0
IMTS-Mixer: Mixer-Networks for Irregular Multivariate Time Series Forecasting—0
Model-free system identification of surface ships in waves via Hankel dynamic mode decomposition with control—0
On the Query Complexity of Verifier-Assisted Language Generation—0
Collaborative Deterministic-Probabilistic Forecasting for Real-World Spatiotemporal Systems—0
Practical Topics in Optimization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified