Large Language Model
ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning
Due to the ever-growing model size, the standard full fine-tuning based task adaptation strategy becomes prohibitively costly in terms of model training and storage.
College Students Have Already Changed Forever
A college senior returning to classes this fall has spent nearly their entire undergraduate career under the shadow--or in the embrace--of generative AI. ChatGPT first launched in November 2022, when that student was a freshman. As a department chair at Washington University in St. Louis, I witnessed the chaos it unleashed on campus. Students weren't sure what AI could do, or which uses were appropriate. Faculty were blindsided by how effectively ChatGPT could write papers and do homework.
A Framework for Data-Centric Biomedical Natural Language Processing Jason Alan Fries 1 Leon Weber
Prompting offers new opportunities for constructing meta-datasets that capture desirable language reasoning skills. In the general NLP domain, data-centric methods have benefited from community efforts such as Hugging Face's datasets hub [
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation--Supplementary Material -- 1 Bayesian Regression for DICE Coefficient
The L-1 regression problem can be interpreted as maximum likelihood with a Laplacian error model. By taking negative log on Eq. 1, we have, ln P (t
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
The empirical gains can be striking.
Flamingo: a Visual Language Model for Few-Shot Learning Jean-Baptiste Alayrac *, Jeff Donahue * Pauline Luc * Antoine Miech
They are mainly found in Chile.