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 476–500 of 4891 papers

TitleStatusHype
Robust MPC for Uncertain Linear Systems -- Combining Model Adaptation and Iterative LearningCode1
Influence Maximization in Temporal Social Networks with a Cold-Start Problem: A Supervised ApproachCode0
Fast-Powerformer: A Memory-Efficient Transformer for Accurate Mid-Term Wind Power Forecasting—0
Focus on Local: Finding Reliable Discriminative Regions for Visual Place RecognitionCode1
Mavors: Multi-granularity Video Representation for Multimodal Large Language Model—0
CAT: A Conditional Adaptation Tailor for Efficient and Effective Instance-Specific Pansharpening on Real-World Data—0
Attention GhostUNet++: Enhanced Segmentation of Adipose Tissue and Liver in CT ImagesCode1
Computationally Efficient State and Model Estimation via Interval Observers for Partially Unknown Systems—0
Ride-pool Assignment Algorithms: Modern Implementation and Swapping Heuristics—0
DTFSal: Audio-Visual Dynamic Token Fusion for Video Saliency Prediction—0
Can LLMs Revolutionize the Design of Explainable and Efficient TinyML Models?—0
Enhancing Mathematical Reasoning in Large Language Models with Self-Consistency-Based Hallucination Detection—0
OmniMamba4D: Spatio-temporal Mamba for longitudinal CT lesion segmentation—0
Integrated GARCH-GRU in Financial Volatility Forecasting—0
Fine-tuning a Large Language Model for Automating Computational Fluid Dynamics SimulationsCode1
HER2 Expression Prediction with Flexible Multi-Modal Inputs via Dynamic Bidirectional Reconstruction—0
Successive Jump and Mode Decomposition—0
Slicing the Gaussian Mixture Wasserstein DistanceCode0
Graph Reduction with Unsupervised Learning in Column Generation: A Routing Application—0
Reinforcement Learning-Driven Plant-Wide Refinery Planning Using Model Decomposition—0
TensorNEAT: A GPU-accelerated Library for NeuroEvolution of Augmenting TopologiesCode3
Hypergraph Vision Transformers: Images are More than Nodes, More than Edges—0
Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical ImagingCode1
SAEs Can Improve Unlearning: Dynamic Sparse Autoencoder Guardrails for Precision Unlearning in LLMs—0
How to Detect and Defeat Molecular Mirage: A Metric-Driven Benchmark for Hallucination in LLM-based Molecular Comprehension—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified