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 776–800 of 4891 papers

TitleStatusHype
Accelerating Focal Search in Multi-Agent Path Finding with Tighter Lower BoundsCode0
Seeded Poisson Factorization: Leveraging domain knowledge to fit topic modelsCode0
COMMA: Coordinate-aware Modulated Mamba Network for 3D Dispersed Vessel SegmentationCode0
DQO-MAP: Dual Quadrics Multi-Object mapping with Gaussian SplattingCode1
Union of Experts: Adapting Hierarchical Routing to Equivalently Decomposed TransformerCode0
Nonlinear energy-preserving model reduction with lifting transformations that quadratize the energy—0
Enabling Fast, Accurate, and Efficient Real-Time Genome Analysis via New Algorithms and Techniques—0
Multi-Step Deep Koopman Network (MDK-Net) for Vehicle Control in Frenet Frame—0
Correcting Mode Proportion Bias in Generalized Bayesian Inference via a Weighted Kernel Stein Discrepancy—0
Uplink Transmission Design for Fluid Antenna-Enabled Multiuser MIMO Systems with Imperfect CSI—0
ECG-EmotionNet: Nested Mixture of Expert (NMoE) Adaptation of ECG-Foundation Model for Driver Emotion Recognition—0
Perceptual Motor Learning with Active Inference Framework for Robust Lateral Control—0
Soybean Disease Detection via Interpretable Hybrid CNN-GNN: Integrating MobileNetV2 and GraphSAGE with Cross-Modal Attention—0
From Claims to Evidence: A Unified Framework and Critical Analysis of CNN vs. Transformer vs. Mamba in Medical Image SegmentationCode1
Enhancing Multi-hop Reasoning in Vision-Language Models via Self-Distillation with Multi-Prompt Ensembling—0
Efficient or Powerful? Trade-offs Between Machine Learning and Deep Learning for Mental Illness Detection on Social Media—0
PEO: Improving Bi-Factorial Preference Alignment with Post-Training Policy Extrapolation—0
MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shiftingCode1
TAET: Two-Stage Adversarial Equalization Training on Long-Tailed DistributionsCode1
Evaluation of adaptive sampling methods in scenario generation for virtual safety impact assessment of pre-crash safety systems—0
Minimax Optimal Reinforcement Learning with Quasi-Optimism—0
Solving Satisfiability Modulo Counting Exactly with Probabilistic Circuits—0
Towards Efficient Educational Chatbots: Benchmarking RAG Frameworks—0
QDCNN: Quantum Deep Learning for Enhancing Safety and Reliability in Autonomous Transportation Systems—0
Optimizing Parameter Estimation for Electrochemical Battery Model: A Comparative Analysis of Operating Profiles on Computational Efficiency and Accuracy—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified