Paper Citation Record · LEDGER

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation

As of 9 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2507.04864.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2507.04864 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:42:05.807116Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:42:04.907340Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T19:42:06.037425Z

Reference resolution

37 of 37 outbound references displayed

verified exact3
verified fuzzy27
unresolved5
parse uncertain0
malformed identifier2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d1808b18-0661-43f0-b915-983e903f8820 · outbound

This paper cites In the field of music generation, these models have to capture complex distributions that define elements such as melody, rhythm and harmony.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation In the field of music generation, these models have to capture complex distributions that define elements such as melody, rhythm and harmony

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.248854Z

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Observation d8868fac-aabc-4b14-b2ca-78767d9dc256 · outbound

This paper cites Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:42:06.040076Z

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Observation 6468a30d-b0eb-4dc5-adc4-de66e817f8e7 · outbound

This paper cites The underlying principle transfers natu- rally to the audio domain, and in this work we explore its application to music audio recordings.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation The underlying principle transfers natu- rally to the audio domain, and in this work we explore its application to music audio recordings

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.242013Z

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Observation bc5112d9-f737-4170-91a5-1434459c7698 · outbound

This paper cites This process must be carried out step by step, exactly as in global sampling of diffusion models, and this is where most of the computational effort occurs.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation This process must be carried out step by step, exactly as in global sampling of diffusion models, and this is where most of the computational effort occurs

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.235034Z

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Observation d9166320-e4dc-4cb4-8800-19c138e2600d · outbound

This paper cites an unresolved cited work.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:42:06.227461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 49a64451-d7b6-4943-bda0-ef9f019c2e19 · outbound

This paper cites Music”) and negative prompt (“Low Quality.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Music”) and negative prompt (“Low Quality

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.220740Z

Source-reported events for the cited work

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Observation f096abe9-7620-4808-94a1-f32e947f8413 · outbound

This paper cites Our results show that it is suitable for data augmentation in training a beat and downbeat detector, but more so if only limited train- ing data is available.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Our results show that it is suitable for data augmentation in training a beat and downbeat detector, but more so if only limited train- ing data is available

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.213744Z

Source-reported events for the cited work

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Observation 5c75b639-24b2-4bf6-ae9b-4bb9fb9e43d3 · outbound

This paper cites Denoising diffusion probabilistic models,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Denoising diffusion probabilistic models,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.206560Z

Source-reported events for the cited work

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Observation c272e73f-2a7a-487d-9aae-b8c315fdf398 · outbound

This paper cites Long-form music generation with latent diffusion.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Long-form music generation with latent diffusion

Reference 9

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Source-reported events for the cited work

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Observation d79ef464-05c3-4034-a875-f2c24070f254 · outbound

This paper cites Grad-TTS: A diffusion probabilistic model for text-to-speech,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Grad-TTS: A diffusion probabilistic model for text-to-speech,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.199360Z

Source-reported events for the cited work

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Observation eea7c68b-1987-4948-b056-663d91640b83 · outbound

This paper cites AudioLDM: Text- to-audio generation with latent diffusion models,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation AudioLDM: Text- to-audio generation with latent diffusion models,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.192371Z

Source-reported events for the cited work

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Observation e2ebaeed-680d-448d-ad4b-1169697aa6b8 · outbound

This paper cites Boomerang: Local sampling on image manifolds using dif- fusion models,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Boomerang: Local sampling on image manifolds using dif- fusion models,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.185454Z

Source-reported events for the cited work

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Observation 796cd92a-29b8-4ffa-9ddb-3af79d29ea54 · outbound

This paper cites WaveNet: A Generative Model for Raw Audio.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation WaveNet: A Generative Model for Raw Audio

Reference 13

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Source-reported events for the cited work

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Observation c4eacf3d-dddd-4251-bebd-33ff4979c654 · outbound

This paper cites Jukebox: A Generative Model for Music.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Jukebox: A Generative Model for Music

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T19:42:05.753964Z

Source-reported events for the cited work

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Observation 454a5f1d-1387-4abc-938e-76beae4a2f71 · outbound

This paper cites Musika! Fast infinite waveform music generation,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Musika! Fast infinite waveform music generation,

Reference 15

Resolution: verified exact; doi, observed 2026-08-06T19:42:05.835613Z

Source-reported events for the cited work

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Observation cdd8ea06-aad3-4b7e-bc8f-9c01f9b67068 · outbound

This paper cites Masked audio generation using a single non-autoregressive transformer,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Masked audio generation using a single non-autoregressive transformer,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.177960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c7383deb-4504-42ac-a612-59675c152dbe · outbound

This paper cites High fidelity neural audio compression,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation High fidelity neural audio compression,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.170839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 826aa547-0dea-492b-8444-6361f0a54207 · outbound

This paper cites Fast timing-conditioned latent audio diffusion,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Fast timing-conditioned latent audio diffusion,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.164039Z

Source-reported events for the cited work

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Observation ae78b7eb-5dcb-45c1-acba-f41672fd8bb8 · outbound

This paper cites U-net: Con- volutional networks for biomedical image segmenta- tion,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation U-net: Con- volutional networks for biomedical image segmenta- tion,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.157271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7326e643-3ce1-461c-9e41-c87b7d42f310 · outbound

This paper cites Moûsai: Efficient text-to-music diffusion models,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Moûsai: Efficient text-to-music diffusion models,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.150563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2acf8ad3-4c79-40d3-8278-6d2e4d1292ed · outbound

This paper cites Stable Audio Open.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Stable Audio Open

Reference 21

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Source-reported events for the cited work

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Observation 8d81a95c-d2d9-48d3-b19b-af365c7691c9 · outbound

This paper cites SDEdit: Guided image synthesis and editing with stochastic differential equations,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation SDEdit: Guided image synthesis and editing with stochastic differential equations,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.142512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 07862254-a795-414b-bd0f-3c5cdfa2bca0 · outbound

This paper cites Come-closer-diffuse- faster: Accelerating conditional diffusion models for inverse problems through stochastic contraction,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Come-closer-diffuse- faster: Accelerating conditional diffusion models for inverse problems through stochastic contraction,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.135400Z

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Observation c952012f-a298-4bdf-818c-a646a4d3bd9d · outbound

This paper cites RoFormer: Enhanced transformer with rotary position embedding,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation RoFormer: Enhanced transformer with rotary position embedding,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.082742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bc275777-a7ea-4336-b2ce-689158f676a7 · outbound

This paper cites Truncated diffusion probabilistic models and diffusion-based ad- versarial auto-encoders,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Truncated diffusion probabilistic models and diffusion-based ad- versarial auto-encoders,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.128195Z

Source-reported events for the cited work

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Observation aa06b94e-c89a-455d-ac5f-3d7cb6ba890f · outbound

This paper cites Consistency models,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Consistency models,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.120868Z

Source-reported events for the cited work

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Observation fb1a61ac-e052-44ad-9034-5b734a75a4be · outbound

This paper cites Score-based generative modeling through stochastic differen- tial equations,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Score-based generative modeling through stochastic differen- tial equations,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.113841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cc4abd26-9978-41d6-8a05-e6b3f7ece912 · outbound

This paper cites DPM-solver: A fast ODE solver for diffusion probabilistic model sampling in around 10 steps,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation DPM-solver: A fast ODE solver for diffusion probabilistic model sampling in around 10 steps,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.106646Z

Source-reported events for the cited work

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Observation b1df1cac-c945-47e5-a924-a233392f159c · outbound

This paper cites DPM-solver++: Fast solver for guided sampling of diffusion probabilistic models,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation DPM-solver++: Fast solver for guided sampling of diffusion probabilistic models,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.098789Z

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Observation 90fb5d4f-f807-46de-9b78-909a2e739ea2 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.090409Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5f72c9a0-7853-4046-a438-43865e35e9c1 · outbound

This paper cites Neural networks fail to learn periodic functions and how to fix it,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Neural networks fail to learn periodic functions and how to fix it,

Reference 31

Resolution: verified exact; raw_fallback, observed 2026-08-06T19:42:05.932563Z

Source-reported events for the cited work

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Observation 9acc4f47-0708-488f-84e6-812caa4ca654 · outbound

This paper cites Progressive distil- lation for fast sampling of diffusion mod- els,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Progressive distil- lation for fast sampling of diffusion mod- els,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.073803Z

Source-reported events for the cited work

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Observation b5c1b249-b8f3-4df9-8027-f53aff2b3566 · outbound

This paper cites librosa: Audio and music signal analysis in python,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation librosa: Audio and music signal analysis in python,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.065186Z

Source-reported events for the cited work

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Observation 633124e0-4bd7-4fc1-afba-20bcb9a93e46 · outbound

This paper cites mir_eval: A transparent implementation of common MIR metrics,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation mir_eval: A transparent implementation of common MIR metrics,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.056135Z

Source-reported events for the cited work

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Observation 5af2636d-7a02-4421-ad98-7ab35de0805b · outbound

This paper cites Swing ratio estimation,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Swing ratio estimation,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:42:06.047606Z

Source-reported events for the cited work

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Observation 72efc1f5-f59c-4da1-ad06-ca8a0eb8ecdf · outbound

This paper cites Beat this! Accurate beat tracking without DBN postprocessing,.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Beat this! Accurate beat tracking without DBN postprocessing,

Reference 37

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Source-reported events for the cited work

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Observation 98ed8f4e-dd40-4530-8685-5fedd3db0441 · outbound

This paper cites Available: https://doi.org/10.1109/ CVPR52688.2022.01209.

Music Boomerang: Reusing Diffusion Models for Data Augmentation and Audio Manipulation Available: https://doi.org/10.1109/ CVPR52688.2022.01209

Reference 2022

Resolution: malformed identifier; no resolver link, observed 2026-08-06T19:42:05.777321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation d8868fac-aabc-4b14-b2ca-78767d9dc256 · inbound