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 2101–2125 of 4891 papers

TitleStatusHype
An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing—0
Effective Interplay between Sparsity and Quantization: From Theory to Practice—0
Spectrum-Aware Parameter Efficient Fine-Tuning for Diffusion ModelsCode0
YotoR-You Only Transform One Representation—0
TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes—0
Hierarchical Object-Centric Learning with Capsule Networks—0
MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution ShiftsCode0
DecomCAM: Advancing Beyond Saliency Maps through Decomposition and IntegrationCode0
CiliaGraph: Enabling Expression-enhanced Hyper-Dimensional Computation in Ultra-Lightweight and One-Shot Graph Classification on Edge—0
Use of Boosting Algorithms in Household-Level Poverty Measurement: A Machine Learning Approach to Predict and Classify Household Wealth Quintiles in the Philippines—0
Combining Off-White and Sparse Black Models in Multi-step Physics-based Systems Identification -- EXTENDED VERSION—0
SoundCTM: Unifying Score-based and Consistency Models for Full-band Text-to-Sound GenerationCode2
Universal and Extensible Language-Vision Models for Organ Segmentation and Tumor Detection from Abdominal Computed TomographyCode4
An Innovative Networks in Federated Learning—0
PromptWizard: Task-Aware Prompt Optimization FrameworkCode7
Long Context is Not Long at All: A Prospector of Long-Dependency Data for Large Language ModelsCode2
Cross-Context Backdoor Attacks against Graph Prompt LearningCode0
On Fairness of Low-Rank Adaptation of Large ModelsCode0
Spectral-Refiner: Accurate Fine-Tuning of Spatiotemporal Fourier Neural Operator for Turbulent FlowsCode2
Performance evaluation of Reddit Comments using Machine Learning and Natural Language Processing methods in Sentiment Analysis—0
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation—0
CLAQ: Pushing the Limits of Low-Bit Post-Training Quantization for LLMsCode0
Trajectory Data Suffices for Statistically Efficient Learning in Offline RL with Linear q^π-Realizability and Concentrability—0
Probabilistic Graph Rewiring via Virtual NodesCode0
Enhancing Fast Feed Forward Networks with Load Balancing and a Master Leaf NodeCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified