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Showing 2001–2025 of 5629 papers

TitleStatusHype
Efficient Distillation of Classifier-Free Guidance using AdaptersCode0
Global Context Is All You Need for Parallel Efficient Tractography Parcellation—0
Fine-Tuning LLMs for Report Summarization: Analysis on Supervised and Unsupervised Data—0
AttFC: Attention Fully-Connected Layer for Large-Scale Face Recognition with One GPU—0
Are We There Yet? A Measurement Study of Efficiency for LLM Applications on Mobile Devices—0
A Mesh Is Worth 512 Numbers: Spectral-domain Diffusion Modeling for High-dimension Shape Generation—0
Real-Time Semantic Segmentation of Aerial Images Using an Embedded U-Net: A Comparison of CPU, GPU, and FPGA Workflows—0
Training and Inference Efficiency of Encoder-Decoder Speech Models—0
Symbolic Mixture-of-Experts: Adaptive Skill-based Routing for Heterogeneous Reasoning—0
Eventprop training for efficient neuromorphic applications—0
Wanda++: Pruning Large Language Models via Regional GradientsCode0
Fine-Tuning Florence2 for Enhanced Object Detection in Un-constructed Environments: Vision-Language Model Approach—0
Predictable Scale: Part I -- Optimal Hyperparameter Scaling Law in Large Language Model Pretraining—0
Partial Convolution Meets Visual Attention—0
JamMa: Ultra-lightweight Local Feature Matching with Joint Mamba—0
Memory and Bandwidth are All You Need for Fully Sharded Data Parallel—0
CoServe: Efficient Collaboration-of-Experts (CoE) Model Inference with Limited Memory—0
Category-level Meta-learned NeRF Priors for Efficient Object Mapping—0
OceanSim: A GPU-Accelerated Underwater Robot Perception Simulation Framework—0
Open-source framework for detecting bias and overfitting for large pathology imagesCode0
KurTail : Kurtosis-based LLM Quantization—0
A Reconfigurable Stream-Based FPGA Accelerator for Bayesian Confidence Propagation Neural Networks—0
Cauchy Random Features for Operator Learning in Sobolev SpaceCode0
Floorplan-SLAM: A Real-Time, High-Accuracy, and Long-Term Multi-Session Point-Plane SLAM for Efficient Floorplan Reconstruction—0
Supporting the development of Machine Learning for fundamental science in a federated Cloud with the AI_INFN platform—0
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