2.3k citations · 2.3k across the 3 of their papers we have counts for
3 papers
cs.LG2023
Enabling tabular deep learning when with an auxiliary knowledge graph
Camilo Ruiz, Hongyu Ren, Kexin Huang +1
Machine learning models exhibit strong performance on datasets with abundant labeled samples. However, for tabular datasets with extremely high -dimensional features but limited…
cs.RO2022★ 5 cited
Leveraging Large (Visual) Language Models for Robot 3D Scene Understanding
William Chen, Siyi Hu, Rajat Talak +1
Abstract semantic 3D scene understanding is a problem of critical importance in robotics. As robots still lack the common-sense knowledge about household objects and locations of a…
cs.LG2021★ 2.3k cited
On the Opportunities and Risks of Foundation Models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli +111
AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.…