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
A Simple Baseline for Efficient Hand Mesh ReconstructionCode2
BitDecoding: Unlocking Tensor Cores for Long-Context LLMs Decoding with Low-Bit KV CacheCode2
Adaptive Multi-Scale Decomposition Framework for Time Series ForecastingCode2
LoRA-Pro: Are Low-Rank Adapters Properly Optimized?Code2
Attentive Merging of Hidden Embeddings from Pre-trained Speech Model for Anti-spoofing DetectionCode2
GotenNet: Rethinking Efficient 3D Equivariant Graph Neural NetworksCode2
I^2-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene ForecastingCode2
Miipher-2: A Universal Speech Restoration Model for Million-Hour Scale Data RestorationCode2
ClearSight: Visual Signal Enhancement for Object Hallucination Mitigation in Multimodal Large language ModelsCode2
Fast-SNARF: A Fast Deformer for Articulated Neural FieldsCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified