132 citations · 187 across the 10 of their papers we have counts for
10 papers
Decomposer: Learning to Decompile Symbolic Music to Programs
Yewon Kim, Apurva Gandhi, David Chung +2
Musical performance involves executing a set of high-level musical instructions, yet recovering those instructions from the performance is a challenging inverse problem. We present…
A Design Space for Live Music Agents
Yewon Kim, Stephen Brade, Alexander Wang +7
Live music provides a uniquely rich setting for studying creativity and interaction due to its spontaneous nature. The pursuit of live music agents--intelligent systems supporting…
Hookpad Aria: A Copilot for Songwriters
Chris Donahue, Shih-Lun Wu, Yewon Kim +3
We present Hookpad Aria, a generative AI system designed to assist musicians in writing Western pop songs. Our system is seamlessly integrated into Hookpad, a web-based editor desi…
Amuse: Human-AI Collaborative Songwriting with Multimodal Inspirations
Yewon Kim, Sung-Ju Lee, Chris Donahue
Songwriting is often driven by multimodal inspirations, such as imagery, narratives, or existing music, yet songwriters remain unsupported by current music AI systems in incorporat…
Design Opportunities for Explainable AI Paraphrasing Tools: A User Study with Non-native English Speakers
Yewon Kim, Thanh-Long V. Le, Donghwi Kim +2
We investigate how non-native English speakers (NNESs) interact with diverse information aids to assess and select AI-generated paraphrases. We develop ParaScope, an AI paraphrasin…
A Design Space for Intelligent and Interactive Writing Assistants
Mina Lee, Katy Ilonka Gero, John Joon Young Chung +33
In our era of rapid technological advancement, the research landscape for writing assistants has become increasingly fragmented across various research communities. We seek to addr…
SoTTA: Robust Test-Time Adaptation on Noisy Data Streams
Taesik Gong, Yewon Kim, Taeckyung Lee +2
Test-time adaptation (TTA) aims to address distributional shifts between training and testing data using only unlabeled test data streams for continual model adaptation. However, m…
Towards Explainable AI Writing Assistants for Non-native English Speakers
Yewon Kim, Mina Lee, Donghwi Kim +1
We highlight the challenges faced by non-native speakers when using AI writing assistants to paraphrase text. Through an interview study with 15 non-native English speakers (NNESs)…
NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation
Taesik Gong, Jongheon Jeong, Taewon Kim +3
Test-time adaptation (TTA) is an emerging paradigm that addresses distributional shifts between training and testing phases without additional data acquisition or labeling cost; on…
DAPPER: Label-Free Performance Estimation after Personalization for Heterogeneous Mobile Sensing
Taesik Gong, Yewon Kim, Adiba Orzikulova +4
Many applications utilize sensors in mobile devices and machine learning to provide novel services. However, various factors such as different users, devices, and environments impa…