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 981–990 of 4891 papers

TitleStatusHype
PosePilot: An Edge-AI Solution for Posture Correction in Physical Exercises—0
A Unified Framework for Variable Selection in Model-Based Clustering with Missing Not at Random—0
Fast and Accurate Power Load Data Completion via Regularization-optimized Low-Rank Factorization—0
FastMamba: A High-Speed and Efficient Mamba Accelerator on FPGA with Accurate Quantization—0
ASPO: Adaptive Sentence-Level Preference Optimization for Fine-Grained Multimodal Reasoning—0
Faithful Group Shapley ValueCode0
Composable Cross-prompt Essay Scoring by Merging Models—0
LoTA-QAF: Lossless Ternary Adaptation for Quantization-Aware Fine-TuningCode0
Message-Passing State-Space Models: Improving Graph Learning with Modern Sequence Modeling—0
Tropical Geometry Based Edge Detection Using Min-Plus and Max-Plus Algebra—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified