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 11–20 of 4891 papers

TitleStatusHype
YOLOv13: Real-Time Object Detection with Hypergraph-Enhanced Adaptive Visual PerceptionCode5
Continuous Thought MachinesCode5
Comet: Fine-grained Computation-communication Overlapping for Mixture-of-ExpertsCode5
FireRedASR: Open-Source Industrial-Grade Mandarin Speech Recognition Models from Encoder-Decoder to LLM IntegrationCode5
Video Depth Anything: Consistent Depth Estimation for Super-Long VideosCode5
Exploring GLU Expansion Ratios: A Study of Structured Pruning in LLaMA-3.2 ModelsCode5
MambaIRv2: Attentive State Space RestorationCode5
CogView3: Finer and Faster Text-to-Image Generation via Relay DiffusionCode5
Partition Generative Modeling: Masked Modeling Without MasksCode4
High-performance training and inference for deep equivariant interatomic potentialsCode4
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified