28 citations · 36 across the 3 of their papers we have counts for
5 papers
PromptChainer: Chaining Large Language Model Prompts through Visual Programming
Tongshuang Wu, Ellen Jiang, Aaron Donsbach +4
While LLMs can effectively help prototype single ML functionalities, many real-world applications involve complex tasks that cannot be easily handled via a single run of an LLM. Re…
Program Synthesis with Large Language Models
Jacob Austin, Augustus Odena, Maxwell Nye +8
This paper explores the limits of the current generation of large language models for program synthesis in general purpose programming languages. We evaluate a collection of such m…
AI Song Contest: Human-AI Co-Creation in Songwriting
Cheng-Zhi Anna Huang, Hendrik Vincent Koops, Ed Newton-Rex +2
Machine learning is challenging the way we make music. Although research in deep generative models has dramatically improved the capability and fluency of music models, recent work…
Human-Centered Tools for Coping with Imperfect Algorithms during Medical Decision-Making
Carrie J. Cai, Emily Reif, Narayan Hegde +8
Machine learning (ML) is increasingly being used in image retrieval systems for medical decision making. One application of ML is to retrieve visually similar medical images from p…
Similar Image Search for Histopathology: SMILY
Narayan Hegde, Jason D. Hipp, Yun Liu +11
The increasing availability of large institutional and public histopathology image datasets is enabling the searching of these datasets for diagnosis, research, and education. Thou…