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 351–360 of 4891 papers

TitleStatusHype
Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PCCode1
CFT-RAG: An Entity Tree Based Retrieval Augmented Generation Algorithm With Cuckoo FilterCode1
BUFFER: Balancing Accuracy, Efficiency, and Generalizability in Point Cloud RegistrationCode1
FastMap: Fast Queries Initialization Based Vectorized HD Map Reconstruction FrameworkCode1
Exploring Quality and Generalizability in Parameterized Neural Audio EffectsCode1
Cached Multi-Lora Composition for Multi-Concept Image GenerationCode1
Calibrating LLMs with Information-Theoretic Evidential Deep LearningCode1
CAMP: Collaborative Attention Model with Profiles for Vehicle Routing ProblemsCode1
On Fast Simulation of Dynamical System with Neural Vector Enhanced Numerical SolverCode1
Facial Emotion Recognition: State of the Art Performance on FER2013Code1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified