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

Showing 29262950 of 4891 papers

TitleStatusHype
EVI-SAM: Robust, Real-time, Tightly-coupled Event-Visual-Inertial State Estimation and 3D Dense Mapping0
Agent Assessment of Others Through the Lens of Self0
Linear Attention via Orthogonal Memory0
A Multimodal Approach for Advanced Pest Detection and Classification0
Video-based Surgical Skill Assessment using Tree-based Gaussian Process Classifier0
Fast Decision Boundary based Out-of-Distribution DetectorCode0
A Hierarchical Nearest Neighbour Approach to Contextual Bandits0
VideoLCM: Video Latent Consistency Model0
A Kronecker product accelerated efficient sparse Gaussian Process (E-SGP) for flow emulation0
ConSequence: Synthesizing Logically Constrained Sequences for Electronic Health Record GenerationCode0
Reconstruction of Cortical Surfaces with Spherical Topology from Infant Brain MRI via Recurrent Deformation Learning0
R2-Talker: Realistic Real-Time Talking Head Synthesis with Hash Grid Landmarks Encoding and Progressive Multilayer Conditioning0
Accelerating Convolutional Neural Network Pruning via Spatial Aura Entropy0
Guaranteed Trust Region Optimization via Two-Phase KL Penalization0
Efficiently Predicting Protein Stability Changes Upon Single-point Mutation with Large Language Models0
Learning to sample in Cartesian MRI0
Deep Dynamics: Vehicle Dynamics Modeling with a Physics-Constrained Neural Network for Autonomous Racing0
GenQ: Quantization in Low Data Regimes with Generative Synthetic DataCode0
Time-Domain Operational Metrics for Real-time Resilience Assessment in DC Microgrids0
Differentiable Point-based Inverse Rendering0
Foundations for Transfer in Reinforcement Learning: A Taxonomy of Knowledge Modalities0
PLUM: Improving Inference Efficiency By Leveraging Repetition-Sparsity Trade-OffCode0
Divide-and-Conquer Strategy for Large-Scale Dynamic Bayesian Network Structure Learning0
On Significance of Subword tokenization for Low Resource and Efficient Named Entity Recognition: A case study in Marathi0
Token Fusion: Bridging the Gap between Token Pruning and Token Merging0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified