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 171–180 of 4891 papers

TitleStatusHype
LoRA-IR: Taming Low-Rank Experts for Efficient All-in-One Image RestorationCode2
Free Video-LLM: Prompt-guided Visual Perception for Efficient Training-free Video LLMsCode2
Generalized and Efficient 2D Gaussian Splatting for Arbitrary-scale Super-ResolutionCode2
GotenNet: Rethinking Efficient 3D Equivariant Graph Neural NetworksCode2
FLowHigh: Towards Efficient and High-Quality Audio Super-Resolution with Single-Step Flow MatchingCode2
ConvMAE: Masked Convolution Meets Masked AutoencodersCode2
Flow Matching in Latent SpaceCode2
Miipher-2: A Universal Speech Restoration Model for Million-Hour Scale Data RestorationCode2
Agent Attention: On the Integration of Softmax and Linear AttentionCode2
I^2-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene ForecastingCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified