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Home/Authors/Seonghyeon Go

Seonghyeon Go

1 indexed paper

Recent (6 mo)
1
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Publications per year

1
26

Top categories

Sound×1AI×1

Frequent co-authors

Yumin Kim1×

Research Timeline

2026
HAIM: Human-AI Music Datasets for AI Music Production Tracking Benchmark

The paper introduces HAIM, a new benchmark dataset designed to move AI music detection beyond simple binary classification by tracking specific stages and types of AI integration in music production.

Highlighted terms show continued research focus across papers

Papers

cs.SDcs.AIRecentJun 1, 2026

HAIM: Human-AI Music Datasets for AI Music Production Tracking Benchmark

Seonghyeon Go, Yumin Kim

The paper introduces HAIM, a new benchmark dataset designed to move AI music detection beyond simple binary classification by tracking specific stages and types of AI integration in music production.

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