Tag: efficient

Jul 11, 2025

KV Cache Steering for Inducing Reasoning in Small Language Models

Jan 01, 2025

Dynamic Resource Allocation in Vision

Jul 29, 2024

Apple Intelligence Foundation Language Models

efficient_dl

Jun 24, 2024

Building on Efficient Foundations - Effectively Training LLMs with Structured Feedforward Layers

Jun 04, 2024

Block Transformer - Global-to-Local Language Modeling for Fast Inference

Apr 21, 2024

Mixture of LoRa Experts

Apr 12, 2024

Scaling (Down) CLIP - A Comprehensive Analysis of Data, Architecture, and Training Strategies

Apr 03, 2024

Talaria - Interactively Optimizing Machine Learning Models for Efficient Inference

efficient_dl

Mar 29, 2024

Efficient Modulation for Vision Networks

Mar 29, 2024

Rewrite the Stars

Mar 26, 2024

The Unreasonable Ineffectiveness of the Deeper Layers

Mar 20, 2024

Rotary Position Embedding for Vision Transformer

Feb 17, 2024

On Good Practices for Task-Specific Distillation of Large Pretrained Visual Models

Feb 07, 2024

EfficientViT-SAM - Accelerated Segment Anything Model Without Accuracy Loss

Feb 03, 2024

Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models - A Survey

Jan 20, 2024

LRP-QViT - Mixed-Precision Vision Transformer Quantization via Layer-wise Relevance Propagation

Jan 17, 2024

Vision Mamba - Efficient Visual Representation Learning with Bidirectional State Space Model

Jan 11, 2024

Surgical-DINO - Adapter Learning of Foundation Models for Depth Estimation in Endoscopic Surgery

Jan 09, 2024

Low-Resource Vision Challenges for Foundation Models

Jan 01, 2024

Block Expansion

Jan 01, 2024

Hardware-specific structured pruning

Jan 01, 2024

Maximal pruning and functional recovery

Jan 01, 2024

PyTorch Quantization for TensorRT

Nov 30, 2023

Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models

Nov 28, 2023

MobileCLIP - Fast Image-Text Models through Multi-Modal Reinforced Training

Oct 23, 2023

SAM-CLIP - Merging Vision Foundation Models towards Semantic and Spatial Understanding

Oct 06, 2023

Model Compression in Practice - Lessons Learned from Practitioners Creating On-device Machine Learning Experiences

Jun 15, 2023

Retrospective - EIE - Efficient Inference Engine onSparse and Compressed Neural Network

efficient_dl

Jun 01, 2023

AWQ - Activation-aware Weight Quantization for LLM Compression and Acceleration

Apr 17, 2023

DETRs Beat YOLOs on Real-time Object Detection

Oct 20, 2022

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

Oct 05, 2021

MobileViT - light-weight, general-purpose, and mobile-friendly vision transformer

Jun 17, 2021

LoRA - Low-Rank Adaptation of Large Language Models

Mar 25, 2021

A survey of quantization methods for efficient neural network inference

efficient_dl

Dec 02, 2018

ProxylessNAS - Direct Neural Architecture Search on Target Task and Hardware

Jun 08, 2015

Learning both Weights and Connections for Efficient Neural Networks

Jan 01, 1989

Second Brain

Explorer

Tag: efficient_dl

KV Cache Steering for Inducing Reasoning in Small Language Models

Dynamic Resource Allocation in Vision

Apple Intelligence Foundation Language Models

Building on Efficient Foundations - Effectively Training LLMs with Structured Feedforward Layers

Block Transformer - Global-to-Local Language Modeling for Fast Inference

Mixture of LoRa Experts

Scaling (Down) CLIP - A Comprehensive Analysis of Data, Architecture, and Training Strategies

Talaria - Interactively Optimizing Machine Learning Models for Efficient Inference

Efficient Modulation for Vision Networks

Rewrite the Stars

The Unreasonable Ineffectiveness of the Deeper Layers

Rotary Position Embedding for Vision Transformer

On Good Practices for Task-Specific Distillation of Large Pretrained Visual Models

EfficientViT-SAM - Accelerated Segment Anything Model Without Accuracy Loss

Parameter-Efficient Fine-Tuning for Pre-Trained Vision Models - A Survey

LRP-QViT - Mixed-Precision Vision Transformer Quantization via Layer-wise Relevance Propagation

Vision Mamba - Efficient Visual Representation Learning with Bidirectional State Space Model

Surgical-DINO - Adapter Learning of Foundation Models for Depth Estimation in Endoscopic Surgery

Low-Resource Vision Challenges for Foundation Models

Block Expansion

Hardware-specific structured pruning

Maximal pruning and functional recovery

PyTorch Quantization for TensorRT

Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models

MobileCLIP - Fast Image-Text Models through Multi-Modal Reinforced Training

SAM-CLIP - Merging Vision Foundation Models towards Semantic and Spatial Understanding

Model Compression in Practice - Lessons Learned from Practitioners Creating On-device Machine Learning Experiences

Retrospective - EIE - Efficient Inference Engine onSparse and Compressed Neural Network

AWQ - Activation-aware Weight Quantization for LLM Compression and Acceleration

DETRs Beat YOLOs on Real-time Object Detection

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

MobileViT - light-weight, general-purpose, and mobile-friendly vision transformer

LoRA - Low-Rank Adaptation of Large Language Models

A survey of quantization methods for efficient neural network inference

ProxylessNAS - Direct Neural Architecture Search on Target Task and Hardware

Learning both Weights and Connections for Efficient Neural Networks

Optimal Brain Damage