NEWSLETTER
Precise knowledge distillation through top N reranking
We propose to use n-best reranking to improve sequence-level knowledge distillation (Kim and Rush, 2016), where we extract pseudo-labels for ...
Tag: distillation
What is data set distillation learning? A complete overview
Dataset distillation is an innovative approach that addresses the challenges posed by the increasing size of data sets in machine ...
Merge Vision Foundation models using multitasking distillation
As the repository of publicly available pretrained vision core models (VFMs) such as CLIP, DINOv2, and SAM grows, users face ...
UT Austin and Meta researchers developed SteinDreamer: a breakthrough in text-to-3D asset synthesis using Stein scoring distillation for superior visual quality and accelerated convergence
Recent advances in text-to-image generation driven by diffusion models have sparked interest in text-guided 3D generation, with the goal of ...
This AI article introduces LCM-LoRA: revolutionizing text-to-image generative tasks with advanced latent consistency models and LoRA distillation
Latent diffusion models are generative models used in machine learning, particularly probabilistic modeling. These models aim to capture the underlying ...
Researchers at the University of Washington and Google have developed step-by-step distillation technology to train a dedicated small machine learning model with less data
In recent years, large language models (LLMs) have revolutionized the field of natural language processing, enabling unprecedented and long-shot learning ...
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