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

Showing 16011625 of 4891 papers

TitleStatusHype
Self-Data Distillation for Recovering Quality in Pruned Large Language Models0
Generalized Group Data Attribution0
Prompt Tuning for Audio Deepfake Detection: Computationally Efficient Test-time Domain Adaptation with Limited Target DatasetCode1
SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement LearningCode2
Retrieval Instead of Fine-tuning: A Retrieval-based Parameter Ensemble for Zero-shot Learning0
Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces0
WGFormer: An SE(3)-Transformer Driven by Wasserstein Gradient Flows for Molecular Ground-State Conformation Prediction0
COrAL: Order-Agnostic Language Modeling for Efficient Iterative RefinementCode0
POPoS: Improving Efficient and Robust Facial Landmark Detection with Parallel Optimal Position SearchCode0
pLDDT-Predictor: High-speed Protein Screening Using Transformer and ESM2Code0
Optimal Downsampling for Imbalanced Classification with Generalized Linear Models0
On the impact of key design aspects in simulated Hybrid Quantum Neural Networks for Earth Observation0
Balancing Innovation and Privacy: Data Security Strategies in Natural Language Processing Applications0
Octopus Inspired Optimization Algorithm: Multi-Level Structures and Parallel Computing StrategiesCode1
Privately Learning from Graphs with Applications in Fine-tuning Large Language ModelsCode0
Think Beyond Size: Adaptive Prompting for More Effective Reasoning0
Scalable Co-Clustering for Large-Scale Data through Dynamic Partitioning and Hierarchical Merging0
Learning Content-Aware Multi-Modal Joint Input Pruning via Bird's-Eye-View Representation0
DreamMesh4D: Video-to-4D Generation with Sparse-Controlled Gaussian-Mesh Hybrid Representation0
Shap-Select: Lightweight Feature Selection Using SHAP Values and RegressionCode1
Gridded Transformer Neural Processes for Large Unstructured Spatio-Temporal Data0
Accelerating the discovery of low-energy structure configurations: a computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning0
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time SeriesCode1
Quantum-Inspired Portfolio Optimization In The QUBO Framework0
Bayesian Estimation and Tuning-Free Rank Detection for Probability Mass Function Tensors0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified