174 citations · 312 across the 7 of their papers we have counts for
13 papers
IGDA: Interactive Graph Discovery through Large Language Model Agents
Alex Havrilla, David Alvarez-Melis, Nicolo Fusi
Large language models () have emerged as a powerful method for discovery. Instead of utilizing numerical data, LLMs utilize associated variable $\textit{semantic met…
Adapting Language Models via Token Translation
Zhili Feng, Tanya Marwah, Nicolo Fusi +2
Modern large language models use a fixed tokenizer to effectively compress text drawn from a source domain. However, applying the same tokenizer to a new target domain often leads…
Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine
Harsha Nori, Yin Tat Lee, Sheng Zhang +15
Generalist foundation models such as GPT-4 have displayed surprising capabilities in a wide variety of domains and tasks. Yet, there is a prevalent assumption that they cannot matc…
Budget-Constrained Bounds for Mini-Batch Estimation of Optimal Transport
David Alvarez-Melis, Nicolò Fusi, Lester Mackey +1
Optimal Transport (OT) is a fundamental tool for comparing probability distributions, but its exact computation remains prohibitive for large datasets. In this work, we introduce n…
On Hard Episodes in Meta-Learning
Samyadeep Basu, Amr Sharaf, Nicolo Fusi +1
Existing meta-learners primarily focus on improving the average task accuracy across multiple episodes. Different episodes, however, may vary in hardness and quality leading to a w…
Rapid Model Architecture Adaption for Meta-Learning
Yiren Zhao, Xitong Gao, Ilia Shumailov +2
Network Architecture Search (NAS) methods have recently gathered much attention. They design networks with better performance and use a much shorter search time compared to traditi…