129 citations · 211 across the 9 of their papers we have counts for
4 papers · 1 filter
Multitask Vision-Language Prompt Tuning
Sheng Shen, Shijia Yang, Tianjun Zhang +4
Prompt Tuning, conditioning on task-specific learned prompt vectors, has emerged as a data-efficient and parameter-efficient method for adapting large pretrained vision-language mo…
Prior Knowledge-Guided Attention in Self-Supervised Vision Transformers
Kevin Miao, Akash Gokul, Raghav Singh +5
Recent trends in self-supervised representation learning have focused on removing inductive biases from training pipelines. However, inductive biases can be useful in settings when…
The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink
David Patterson, Joseph Gonzalez, Urs Hölzle +7
Machine Learning (ML) workloads have rapidly grown in importance, but raised concerns about their carbon footprint. Four best practices can reduce ML training energy by up to 100x…
Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data
Yaoqing Yang, Ryan Theisen, Liam Hodgkinson +4
Selecting suitable architecture parameters and training hyperparameters is essential for enhancing machine learning (ML) model performance. Several recent empirical studies conduct…