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 26–50 of 4891 papers

TitleStatusHype
RaDe-GS: Rasterizing Depth in Gaussian SplattingCode4
High-performance training and inference for deep equivariant interatomic potentialsCode4
LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression ToolkitCode4
Universal and Extensible Language-Vision Models for Organ Segmentation and Tumor Detection from Abdominal Computed TomographyCode4
On the limits of agency in agent-based modelsCode4
TorchRL: A data-driven decision-making library for PyTorchCode4
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of ExpertsCode4
TRIPS: Trilinear Point Splatting for Real-Time Radiance Field RenderingCode4
An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language ModelsCode4
RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization BenchmarkCode4
On the Efficiency of NLP-Inspired Methods for Tabular Deep LearningCode3
Effects of charging and discharging capabilities on trade-offs between model accuracy and computational efficiency in pumped thermal electricity storageCode3
EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image SegmentationCode3
NeuralOM: Neural Ocean Model for Subseasonal-to-Seasonal SimulationCode3
MoC: Mixtures of Text Chunking Learners for Retrieval-Augmented Generation SystemCode3
MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein EmbeddingCode3
DUFOMap: Efficient Dynamic Awareness MappingCode3
Dataset Distillation with Neural Characteristic Function: A Minmax PerspectiveCode3
MetaDE: Evolving Differential Evolution by Differential EvolutionCode3
Nd-BiMamba2: A Unified Bidirectional Architecture for Multi-Dimensional Data ProcessingCode3
Is Mamba Effective for Time Series Forecasting?Code3
Consistency Models Made EasyCode3
CoverM: Read alignment statistics for metagenomicsCode3
LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge DistillationCode3
Human-like Episodic Memory for Infinite Context LLMsCode3
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified