Browse State-of-the-Art › Key Detection
Key Detection
7 papers with code · 0 benchmarks · 1 dataset archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
7 shown of 7 papers with code (15 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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18 Jun 2025 1 repository listedDetailed captions that accurately reflect the characteristics of a music piece can enrich music databases and drive forward research in music AI.
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28 Mar 2025 1 repository listedThis study evaluates the baseline capabilities of Large Language Models (LLMs) like ChatGPT, Claude, and Gemini to learn concepts in music theory through in-context learning and chain-of-thought prompting.
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18 Feb 2025 1 repository listedBuilt on a contrastive learning framework, Myna introduces two key innovations: (1) the use of a Vision Transformer (ViT) on mel-spectrograms as the backbone and (2) a novel data augmentation strategy, token masking,…
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2 Jan 2025 1 repository listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)In this paper, we propose a self-supervised music representation learning model for music understanding.
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28 Nov 2024 1 repository listedCommon ways of adapting music foundation models to downstream tasks are probing and fine-tuning.
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7 Nov 2021 1 repository listedIn recent years, complex convolutional neural network architectures such as the Inception architecture have been shown to offer significant improvements over previous architectures in image classification.
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12 Jul 2021 1 repository listed Syntology ran 3 of 3 samples · 0 unverifiedRelative to representations from conventional MIR models which are pre-trained on tagging, we find that using representations from Jukebox as input features yields 30% stronger performance on average across four MIR…
Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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