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 1761–1770 of 4891 papers

TitleStatusHype
The Power of Negative Zero: Datatype Customization for Quantized Large Language ModelsCode0
Samba-ASR: State-Of-The-Art Speech Recognition Leveraging Structured State-Space Models—0
The Efficiency vs. Accuracy Trade-off: Optimizing RAG-Enhanced LLM Recommender Systems Using Multi-Head Early Exit—0
Quaternionic Reweighted Amplitude Flow for Phase Retrieval in Image Reconstruction—0
Majorization-Minimization Dual Stagewise Algorithm for Generalized Lasso—0
Tree-NET: Enhancing Medical Image Segmentation Through Efficient Low-Level Feature Training—0
Emergency-Brake Simplex: Toward A Verifiably Safe Control-CPS Architecture for Abrupt Runtime Reachability Constraint Changes—0
LCFed: An Efficient Clustered Federated Learning Framework for Heterogeneous Data—0
Task-Driven Fixation Network: An Efficient Architecture with Fixation Selection—0
Dynamic Attention-Guided Context Decoding for Mitigating Context Faithfulness Hallucinations in Large Language Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified