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

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Showing 2151–2200 of 4891 papers

TitleStatusHype
Quadratic Gating Functions in Mixture of Experts: A Statistical Insight—0
Rethinking Graph Transformer Architecture Design for Node Classification—0
A few-shot Label Unlearning in Vertical Federated Learning—0
fastHDMI: Fast Mutual Information Estimation for High-Dimensional Data—0
Large Language Model Evaluation via Matrix Nuclear-NormCode0
Echo State Networks for Spatio-Temporal Area-Level Data—0
SGLP: A Similarity Guided Fast Layer Partition Pruning for Compressing Large Deep ModelsCode0
Ada-K Routing: Boosting the Efficiency of MoE-based LLMs—0
Real-time Monitoring of Lower Limb Movement Resistance Based on Deep Learning—0
Retrieval Instead of Fine-tuning: A Retrieval-based Parameter Ensemble for Zero-shot Learning—0
Self-Data Distillation for Recovering Quality in Pruned Large Language Models—0
Large-scale Multi-objective Feature Selection: A Multi-phase Search Space Shrinking Approach—0
WGFormer: An SE(3)-Transformer Driven by Wasserstein Gradient Flows for Molecular Ground-State Conformation Prediction—0
Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces—0
Generalized Group Data Attribution—0
POPoS: Improving Efficient and Robust Facial Landmark Detection with Parallel Optimal Position SearchCode0
COrAL: Order-Agnostic Language Modeling for Efficient Iterative RefinementCode0
On the impact of key design aspects in simulated Hybrid Quantum Neural Networks for Earth Observation—0
Optimal Downsampling for Imbalanced Classification with Generalized Linear Models—0
pLDDT-Predictor: High-speed Protein Screening Using Transformer and ESM2Code0
Balancing Innovation and Privacy: Data Security Strategies in Natural Language Processing Applications—0
Think Beyond Size: Adaptive Prompting for More Effective Reasoning—0
Privately Learning from Graphs with Applications in Fine-tuning Large Language ModelsCode0
Learning Content-Aware Multi-Modal Joint Input Pruning via Bird's-Eye-View Representation—0
Scalable Co-Clustering for Large-Scale Data through Dynamic Partitioning and Hierarchical Merging—0
DreamMesh4D: Video-to-4D Generation with Sparse-Controlled Gaussian-Mesh Hybrid Representation—0
Gridded Transformer Neural Processes for Large Unstructured Spatio-Temporal Data—0
FLOPS: Forward Learning with OPtimal Sampling—0
Quantum-Inspired Portfolio Optimization In The QUBO Framework—0
Accelerating the discovery of low-energy structure configurations: a computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning—0
Bayesian Estimation and Tuning-Free Rank Detection for Probability Mass Function Tensors—0
Diffusion Models in 3D Vision: A Survey—0
SegINR: Segment-wise Implicit Neural Representation for Sequence Alignment in Neural Text-to-Speech—0
IGroupSS-Mamba: Interval Group Spatial-Spectral Mamba for Hyperspectral Image Classification—0
Granular Ball Twin Support Vector MachineCode0
CR-CTC: Consistency regularization on CTC for improved speech recognition—0
GARLIC: LLM-Guided Dynamic Progress Control with Hierarchical Weighted Graph for Long Document QA—0
SPikE-SSM: A Sparse, Precise, and Efficient Spiking State Space Model for Long Sequences Learning—0
Bisimulation metric for Model Predictive ControlCode0
Upsample or Upweight? Balanced Training on Heavily Imbalanced Datasets—0
Spectral Densities, Structured Noise and Ensemble Averaging within Open Quantum Dynamics—0
Never Mind The No-Ops: Faster and Less Volatile Simulation Modelling of Co-Evolutionary Species Interactions via Spatial Cyclic GamesCode0
Efficient Training of Neural Stochastic Differential Equations by Matching Finite Dimensional Distributions—0
Learning Structured Representations by Embedding Class Hierarchy with Fast Optimal TransportCode0
S7: Selective and Simplified State Space Layers for Sequence Modeling—0
A Training-Free Conditional Diffusion Model for Learning Stochastic Dynamical SystemsCode0
STONE: A Submodular Optimization Framework for Active 3D Object DetectionCode0
Remember and Recall: Associative-Memory-based Trajectory Prediction—0
Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement—0
Efficient Second-Order Neural Network Optimization via Adaptive Trust Region Methods—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified