1 citations · 1 across the 11 of their papers we have counts for
13 papers
Revisiting Input Time-frequency Representations in Multi-pitch Estimation for Vocal Ensembles
Junyoung Koh, Hao-Wen Dong
Multi-pitch estimation in vocal ensembles is challenging because singers occupy overlapping pitch ranges and often sing at closely spaced fundamental frequencies, causing their har…
Neural Audio Codec for Robust Audio Deepfake Detection
Jungwoo Kim, Joonyong Park, Junyoung Koh +1
Audio deepfake detectors are typically evaluated on uncompressed audio, although real-world audio often undergoes low-bitrate coding. In this work, we investigate how audio coding…
Probing Token Spaces under Generator Shift in AI-Generated Music Detection
Joonyong Park, Jungwoo Kim, Junyoung Koh +1
AI-generated music detectors can appear robust on standard benchmark splits, yet their deployments require transfer to generator sources absent during training. We study this probl…
Instrumental Text-to-Music Generation with Auxiliary Conditioning Branches
Junyoung Koh
Text-to-music generation has advanced rapidly, with modern autoregressive and diffusion-based models producing convincing music from natural-language prompts. However, much of this…
MCJudgeBench: A Benchmark for Constraint-Level Judge Evaluation in Multi-Constraint Instruction Following
Jaeyun Lee, Junyoung Koh, Zeynel Tok +2
Multi-constraint instruction following requires verifying whether a response satisfies multiple individual requirements, yet LLM judges are often assessed only through overall-resp…
Jamendo-MT-QA: A Benchmark for Multi-Track Comparative Music Question Answering
Junyoung Koh, Jaeyun Lee, Soo Yong Kim +5
Recent work on music question answering (Music-QA) has primarily focused on single-track understanding, where models answer questions about an individual audio clip using its tags,…
Let Triggers Control: Frequency-Aware Dropout for Effective Token Control
Junyoung Koh, Hoyeon Moon, Dongha Kim +3
Text-to-image models such as Stable Diffusion have achieved unprecedented levels of high-fidelity visual synthesis. As these models advance, personalization of generative models --…
Automatic Inter-document Multi-hop Scientific QA Generation
Seungmin Lee, Dongha Kim, Yuni Jeon +2
Existing automatic scientific question generation studies mainly focus on single-document factoid QA, overlooking the inter-document reasoning crucial for scientific understanding.…
AIBA: Attention-based Instrument Band Alignment for Text-to-Audio Diffusion
Junyoung Koh, Soo Yong Kim, Gyu Hyeong Choi +1
We present AIBA (Attention-In-Band Alignment), a lightweight, training-free pipeline to quantify where text-to-audio diffusion models attend on the time-frequency (T-F) plane. AIBA…
Jamendo-QA: A Large-Scale Music Question Answering Dataset
Junyoung Koh, Soo Yong Kim, Yongwon Choi +1
We introduce Jamendo-QA, a large-scale dataset for Music Question Answering (Music-QA). The dataset is built on freely licensed tracks from the Jamendo platform and is automaticall…
Illustrious: an Open Advanced Illustration Model
Sang Hyun Park, Jun Young Koh, Junha Lee +5
In this work, we share the insights for achieving state-of-the-art quality in our text-to-image anime image generative model, called Illustrious. To achieve high resolution, dynami…
Improving Text Generation on Images with Synthetic Captions
Jun Young Koh, Sang Hyun Park, Joy Song
The recent emergence of latent diffusion models such as SDXL and SD 1.5 has shown significant capability in generating highly detailed and realistic images. Despite their remarkabl…
CAT: Contrastive Adapter Training for Personalized Image Generation
Jae Wan Park, Sang Hyun Park, Jun Young Koh +2
The emergence of various adapters, including Low-Rank Adaptation (LoRA) applied from the field of natural language processing, has allowed diffusion models to personalize image gen…