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 3476–3500 of 4891 papers

TitleStatusHype
Amortized Bayesian Local Interpolation NetworK: Fast covariance parameter estimation for Gaussian Processes—0
Scale-Space Hypernetworks for Efficient Biomedical Imaging—0
Amulet: ReAlignment During Test Time for Personalized Preference Adaptation of LLMs—0
A Multi-Document Coverage Reward for RELAXed Multi-Document Summarization—0
A Multimodal Approach for Advanced Pest Detection and Classification—0
A Multiple Source Hourglass Deep Network for Multi-Focus Image Fusion—0
A Multi-Scale Spatial Attention-Based Zero-Shot Learning Framework for Low-Light Image Enhancement—0
An Accelerated Camera 3DMA Framework for Efficient Urban GNSS Multipath Estimation—0
ARES: An Efficient Algorithm with Recurrent Evaluation and Sampling-Driven Inference for Maximum Independent Set—0
An ADRC-Incorporated Stochastic Gradient Descent Algorithm for Latent Factor Analysis—0
An Algorithm-Hardware Co-Optimized Framework for Accelerating N:M Sparse Transformers—0
YOCO: A Hybrid In-Memory Computing Architecture with 8-bit Sub-PetaOps/W In-Situ Multiply Arithmetic for Large-Scale AI—0
Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler—0
Analysis of Truncated Singular Value Decomposition for Koopman Operator-Based Lane Change Model—0
Analytical Discovery of Manifold with Machine Learning—0
Analytical Formula for Fractional-Order Conditional Moments of Nonlinear Drift CEV Process with Regime Switching: Hybrid Approach with Applications—0
Analytically Tractable Inference in Deep Neural Networks—0
Analytical Models of Frequency and Voltage in Large-Scale All-Inverter Power Systems—0
Analytical results for uncertainty propagation through trained machine learning regression models—0
Analyzing Deep Learning Representations of Point Clouds for Real-Time In-Vehicle LiDAR Perception—0
Identifying and Analyzing Task-Encoding Tokens in Large Language Models—0
An analysis of the derivative-free loss method for solving PDEs—0
An Asymptotic Equation Linking WAIC and WBIC in Singular Models—0
An Attention-LSTM Hybrid Model for the Coordinated Routing of Multiple Vehicles—0
An Autonomous Vision-Based Algorithm for Interplanetary Navigation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified