1.2k citations · 1.3k across the 10 of their papers we have counts for
25 papers
M-VADER: A Model for Diffusion with Multimodal Context
Samuel Weinbach, Marco Bellagente, Constantin Eichenberg +7
We introduce M-VADER: a diffusion model (DM) for image generation where the output can be specified using arbitrary combinations of images and text. We show how M-VADER enables the…
Mind's Eye: Grounded Language Model Reasoning through Simulation
Ruibo Liu, Jason Wei, Shixiang Shane Gu +5
Successful and effective communication between humans and AI relies on a shared experience of the world. By training solely on written text, current language models (LMs) miss the…
Scaling Instruction-Finetuned Language Models
Hyung Won Chung, Le Hou, Shayne Longpre +32
Finetuning language models on a collection of datasets phrased as instructions has been shown to improve model performance and generalization to unseen tasks. In this paper we expl…
BEDS-Bench: Behavior of EHR-models under Distributional Shift--A Benchmark
Anand Avati, Martin Seneviratne, Emily Xue +3
Machine learning has recently demonstrated impressive progress in predictive accuracy across a wide array of tasks. Most ML approaches focus on generalization performance on unseen…
MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records
Zhen Xu, David R. So, Andrew M. Dai
One important challenge of applying deep learning to electronic health records (EHR) is the complexity of their multimodal structure. EHR usually contains a mixture of structured (…
Learnability and Complexity of Quantum Samples
Murphy Yuezhen Niu, Andrew M. Dai, Li Li +5
Given a quantum circuit, a quantum computer can sample the output distribution exponentially faster in the number of bits than classical computers. A similar exponential separation…