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 1226–1250 of 4891 papers

TitleStatusHype
A Light-Weight Framework for Open-Set Object Detection with Decoupled Feature Alignment in Joint SpaceCode2
Enhancing Diffusion Models for High-Quality Image Generation—0
PreMixer: MLP-Based Pre-training Enhanced MLP-Mixers for Large-scale Traffic Forecasting—0
Refining Salience-Aware Sparse Fine-Tuning Strategies for Language ModelsCode0
Lightweight Safety Classification Using Pruned Language Models—0
Threshold Neuron: A Brain-inspired Artificial Neuron for Efficient On-device Inference—0
GaraMoSt: Parallel Multi-Granularity Motion and Structural Modeling for Efficient Multi-Frame Interpolation in DSA ImagesCode1
PASCO (PArallel Structured COarsening): an overlay to speed up graph clustering algorithmsCode0
Rare Event Detection in Imbalanced Multi-Class Datasets Using an Optimal MIP-Based Ensemble Weighting ApproachCode0
A Survey on Inference Optimization Techniques for Mixture of Experts ModelsCode3
Subspace Langevin Monte Carlo—0
Indirect Query Bayesian Optimization with Integrated Feedback—0
E-CAR: Efficient Continuous Autoregressive Image Generation via Multistage Modeling—0
Compressed Sensing Based Residual Recovery Algorithms and Hardware for Modulo Sampling—0
Efficient Oriented Object Detection with Enhanced Small Object Recognition in Aerial Images—0
SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training—0
Deep Learning for Resilient Adversarial Decision Fusion in Byzantine Networks—0
Design of Restricted Normalizing Flow towards Arbitrary Stochastic Policy with Computational Efficiency—0
Core Context Aware Attention for Long Context Language Modeling—0
Efficient Object-centric Representation Learning with Pre-trained Geometric Prior—0
Accelerating Sparse Graph Neural Networks with Tensor Core Optimization—0
The dark side of the forces: assessing non-conservative force models for atomistic machine learningCode2
A partial likelihood approach to tree-based density modeling and its application in Bayesian inference—0
Acceleration and Parallelization Methods for ISRS EGN Model—0
Optimal Gradient Checkpointing for Sparse and Recurrent Architectures using Off-Chip Memory—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified