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 2131–2140 of 4891 papers

TitleStatusHype
Learning to Control the Smoothness of Graph Convolutional Network Features—0
TreeBoN: Enhancing Inference-Time Alignment with Speculative Tree-Search and Best-of-N Sampling—0
Tensor Decomposition with Unaligned Observations—0
Supervised Kernel ThinningCode0
RemoteDet-Mamba: A Hybrid Mamba-CNN Network for Multi-modal Object Detection in Remote Sensing Images—0
Efficient Vision-Language Models by Summarizing Visual Tokens into Compact Registers—0
Learning Efficient Representations of Neutrino Telescope EventsCode0
Adaptive and oblivious statistical adversaries are equivalent—0
DiRecNetV2: A Transformer-Enhanced Network for Aerial Disaster Recognition—0
The Latent Road to Atoms: Backmapping Coarse-grained Protein Structures with Latent Diffusion—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified