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 2941–2950 of 4891 papers

TitleStatusHype
TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems—0
TACO-RL: Task Aware Prompt Compression Optimization with Reinforcement Learning—0
Taipan: Efficient and Expressive State Space Language Models with Selective Attention—0
TALL -- A Trainable Architecture for Enhancing LLM Performance in Low-Resource Languages—0
Taming Feed-forward Reconstruction Models as Latent Encoders for 3D Generative Models—0
Target Localization with Coprime Multistatic MIMO Radar via Coupled Canonical Polyadic Decomposition Based on Joint Eigenvalue Decomposition—0
Task Aware Modulation using Representation Learning: An Approach for Few Shot Learning in Environmental Systems—0
Task-Driven Fixation Network: An Efficient Architecture with Fixation Selection—0
TASL-Net: Tri-Attention Selective Learning Network for Intelligent Diagnosis of Bimodal Ultrasound Video—0
Taylor-Expansion-Based Robust Power Flow in Unbalanced Distribution Systems: A Hybrid Data-Aided Method—0
Show:102550
← PrevPage 295 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified