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Paper Citation Record · LEDGER

Equivariant Music Transformer

As of 8 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2608.03920.

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

pith.paper-citation-record.v1
2608.03920 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T05:49:20.969039Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T05:49:20.757909Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T05:49:21.587988Z

Reference resolution

43 of 43 outbound references displayed

  • verified exact7
  • verified fuzzy25
  • unresolved9
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5e4c95c2-6ded-4c24-b4de-932577de86af · outbound

This paper cites Equivariant Music Transformer.

Equivariant Music Transformer Equivariant Music Transformer

Reference 1

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verified exact
local_arxiv, observed 2026-08-05T05:49:21.593059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 22720cf1-b337-42e0-b44d-8baa6eb9704d · outbound

This paper cites The auxiliary loss not only pro- duces music representations that align with human perception of music, but also directly improves the model’s generative capabilities.

Equivariant Music Transformer The auxiliary loss not only pro- duces music representations that align with human perception of music, but also directly improves the model’s generative capabilities

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f9adbd30-d78c-4996-9356-d0c7ee7a6947 · outbound

This paper cites To the best of our knowledge, this provides the first empirical evidence that equivariance does not emerge from scaling.

Equivariant Music Transformer To the best of our knowledge, this provides the first empirical evidence that equivariance does not emerge from scaling

Reference 3

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Observation a05c296a-f0d1-44d8-b195-9d0e800a2064 · outbound

This paper cites Moreover, we confirm that EMT maintains consistent generative quality and smoothness under musically-shifted prompts, while the baseline exhibits more significant degradations.

Equivariant Music Transformer Moreover, we confirm that EMT maintains consistent generative quality and smoothness under musically-shifted prompts, while the baseline exhibits more significant degradations

Reference 4

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raw_fallback, observed 2026-08-05T05:49:21.985989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 321a2653-1b48-4d52-9ae5-10ef59d38135 · outbound

This paper cites an unresolved cited work.

Equivariant Music Transformer Unresolved cited work

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T05:49:20.777812Z digest=sha256:2d080c44a1e083274f75d3c60a4b1dd43cc33f93a2a2ae9c8a218df76d0fd911

Observation fcb52267-b101-4b15-83c5-54d4c8055607 · outbound

This paper cites an unresolved cited work.

Equivariant Music Transformer Unresolved cited work

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 412a65bd-cc07-43b3-96b9-0abc4792dc0b · outbound

This paper cites For example, transposing a melody by 2 semitones should shift the output pitch distri- bution by the same amount.

Equivariant Music Transformer For example, transposing a melody by 2 semitones should shift the output pitch distri- bution by the same amount

Reference 7

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raw_fallback, observed 2026-08-05T05:49:21.972321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4fb6b882-27ec-4ba6-b580-6e17ca23b11d · outbound

This paper cites The main branch to the left rep- resents a generative transformer, which is trained to au- toregressively predict the music tokenx t at the next stept.

Equivariant Music Transformer The main branch to the left rep- resents a generative transformer, which is trained to au- toregressively predict the music tokenx t at the next stept

Reference 8

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7c24a61e-1ac3-44ff-a936-698013823b16 · outbound

This paper cites We also conduct a listening test to evaluate the robustness of symbolic music transformers under musically-shifted in- put prompts.

Equivariant Music Transformer We also conduct a listening test to evaluate the robustness of symbolic music transformers under musically-shifted in- put prompts

Reference 9

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 1d653911-8f82-43eb-8235-e00d413ef41a · outbound

This paper cites We conduct our ablation studies using the clean subset (LMD clean) due to computation constraints.

Equivariant Music Transformer We conduct our ablation studies using the clean subset (LMD clean) due to computation constraints

Reference 10

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Observation 177b657e-b782-428b-bdb5-11e5377c8566 · outbound

This paper cites Overall, models incorporating auxiliary signals (Model 3-.

Equivariant Music Transformer Overall, models incorporating auxiliary signals (Model 3-

Reference 11

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c7abec99-14b8-4460-959e-fd3b770e354f · outbound

This paper cites This shows that explic- itly adding an equivariance regularizer not only enforces structural coherence but also directly improves the model’s generative capabilities.

Equivariant Music Transformer This shows that explic- itly adding an equivariance regularizer not only enforces structural coherence but also directly improves the model’s generative capabilities

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T05:49:20.807599Z digest=sha256:6a2f6d9fccb78561474cbe4b9582af4c1fcb7fbcc3c1abb9aae26ac164876ce8

Observation 176fc201-0233-4f05-8eb5-89e041a611e2 · outbound

This paper cites an unresolved cited work.

Equivariant Music Transformer Unresolved cited work

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 1372dbd6-c977-40d7-b47a-1b7343023695 · outbound

This paper cites We also used Claude Code to assist in implementing the code- base, all of which was manually verified for correctness by the first author.

Equivariant Music Transformer We also used Claude Code to assist in implementing the code- base, all of which was manually verified for correctness by the first author

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 10e4d1a7-483b-45d4-a342-7fac6ce7f0b6 · outbound

This paper cites QMERC20.565.DSEECS25.027).

Equivariant Music Transformer QMERC20.565.DSEECS25.027)

Reference 15

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 68283645-ceb7-438e-9c9b-336d4c09e334 · outbound

This paper cites Group equivariant convolutional networks,.

Equivariant Music Transformer Group equivariant convolutional networks,

Reference 16

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Observation 4eb65a3f-1686-455a-af6b-b6daa1a43581 · outbound

This paper cites Scale and contour: Two components of a theory of memory for melodies,.

Equivariant Music Transformer Scale and contour: Two components of a theory of memory for melodies,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation dde93c84-df5c-462b-8b0f-c7ad7ea55a98 · outbound

This paper cites PESTO: real-time pitch estimation with self-supervised transposition- equivariant objective,.

Equivariant Music Transformer PESTO: real-time pitch estimation with self-supervised transposition- equivariant objective,

Reference 18

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doi, observed 2026-08-05T05:49:21.149404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4eae16e7-64f1-4f3f-888e-2548f4dc9892 · outbound

This paper cites Equivariant self-supervision for musical tempo estimation,.

Equivariant Music Transformer Equivariant self-supervision for musical tempo estimation,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T05:49:20.847060Z digest=sha256:78695bfdb9cf38701e6a6c266d72cd8d3919b4792f39b02f999586f6a134dc54

Observation 0e4c7df0-3a5a-4642-93e0-785863f35be4 · outbound

This paper cites Adapting pitch-based self supervised learning models for tempo estimation,.

Equivariant Music Transformer Adapting pitch-based self supervised learning models for tempo estimation,

Reference 20

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T05:49:20.852586Z digest=sha256:e9348d7f51dd0ee6aaf6e69c325fdac30c7597f7f267e4df3fb9db2c7433bb54

Observation bdcfd2da-3c7b-4ffa-a8e8-8043cecc6bb7 · outbound

This paper cites A predictive model for music based on learned interval representations,.

Equivariant Music Transformer A predictive model for music based on learned interval representations,

Reference 21

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Observation 91ef99a3-a12f-4bc7-9e25-ff7c802bb65d · outbound

This paper cites STONE: self- supervised tonality estimator,.

Equivariant Music Transformer STONE: self- supervised tonality estimator,

Reference 22

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doi, observed 2026-08-05T05:49:21.133501Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 93337f28-2a37-4b64-a65d-8ff2be785cb9 · outbound

This paper cites A domain- knowledge-inspired music embedding space and a novel attention mechanism for symbolic mu- sic modeling,.

Equivariant Music Transformer A domain- knowledge-inspired music embedding space and a novel attention mechanism for symbolic mu- sic modeling,

Reference 23

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Observation aa02186a-6ab0-49f9-9426-450db80f2a6e · outbound

This paper cites On the importance of time and pitch relativity for transformer- based symbolic music generation,.

Equivariant Music Transformer On the importance of time and pitch relativity for transformer- based symbolic music generation,

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 04ac7717-071a-486b-bb23-4c4b3574bc45 · outbound

This paper cites Moonbeam: A MIDI Foundation Model Using Both Absolute and Relative Music Attributes.

Equivariant Music Transformer Moonbeam: A MIDI Foundation Model Using Both Absolute and Relative Music Attributes

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:49:20.876546Z digest=sha256:40e98f28880a64d509e610e55406b389086dea17169f08179f99661da15281e2

Observation 2d995503-f0fa-4cde-a595-eb21003343be · outbound

This paper cites F-stripe: Fast structure-informed positional encoding for sym- bolic music generation,.

Equivariant Music Transformer F-stripe: Fast structure-informed positional encoding for sym- bolic music generation,

Reference 26

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T05:49:20.881809Z digest=sha256:939a038c65b79c5c3aaa026636f82082f04e106c9d84683a39828fe9b0bb86b5

Observation 216959ff-32f8-4db2-b5b3-8f73f9351eb9 · outbound

This paper cites Music transformer: Gen- erating music with long-term structure,.

Equivariant Music Transformer Music transformer: Gen- erating music with long-term structure,

Reference 28

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 3def1b90-ae3e-4399-9556-8869f96bc8f0 · outbound

This paper cites Mustango: Toward con- trollable text-to-music generation,.

Equivariant Music Transformer Mustango: Toward con- trollable text-to-music generation,

Reference 29

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Observation a70538d8-9779-4e7e-84cc-9d88772f9ad2 · outbound

This paper cites Lakhnes: Improving multi- instrumental music generation with cross-domain pre-training,.

Equivariant Music Transformer Lakhnes: Improving multi- instrumental music generation with cross-domain pre-training,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T05:49:20.900569Z digest=sha256:8364b0144cea54edffa8b4b2b32352806b8bd487ad18e5c567d4a19f9867ff41

Observation a312eeff-99ec-4169-9a5a-9b6ec0ee2379 · outbound

This paper cites Scaling self-supervised represen- tation learning for symbolic piano performance,.

Equivariant Music Transformer Scaling self-supervised represen- tation learning for symbolic piano performance,

Reference 31

Resolution
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doi, observed 2026-08-05T05:49:21.118822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 3ebab1d5-db3b-4dc0-8d15-a9b9274b5dbe · outbound

This paper cites Anticipatory music transformer,.

Equivariant Music Transformer Anticipatory music transformer,

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T05:49:20.910657Z digest=sha256:f347c4dc56ba184500341408de0b0db6c28debb12fe658ffd0bf093c01f11391

Observation 13dbabac-afc7-4cb0-abaf-0ccae35e839f · outbound

This paper cites Leave- one-equivariant: Alleviating invariance-related in- formation loss in contrastive music representa- tions,.

Equivariant Music Transformer Leave- one-equivariant: Alleviating invariance-related in- formation loss in contrastive music representa- tions,

Reference 33

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raw_fallback, observed 2026-08-05T05:49:21.704954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T05:49:20.915215Z digest=sha256:7f6574a2e8319d9ca8cf7f0a3adc3e99cd5627fab35cb0d07c8470248fb06d8d

Observation 2d6e7ade-1c9c-4def-9474-6aaae7465aa2 · outbound

This paper cites an unresolved cited work.

Equivariant Music Transformer Unresolved cited work

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:49:20.919837Z digest=sha256:e1e61d0fb0678d2a6418af884e1f0efa934bc6f993f81da881ad6b6cc8537d89

Observation bf458100-e374-451b-ac66-f9ee9364d806 · outbound

This paper cites Audio synthesizer inversion in symmetric parameter spaces with approximately equivariant flow matching,.

Equivariant Music Transformer Audio synthesizer inversion in symmetric parameter spaces with approximately equivariant flow matching,

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 3a013cca-62c4-4f32-838d-457b0acc2cc2 · outbound

This paper cites Position paper: Towards a unified representation evaluation framework beyond downstream tasks,.

Equivariant Music Transformer Position paper: Towards a unified representation evaluation framework beyond downstream tasks,

Reference 36

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f9435cdf-e456-4aee-a49c-9b9708d4d2b3 · outbound

This paper cites Music102: An $D_{12}$-equivariant transformer for chord progression accompaniment.

Equivariant Music Transformer Music102: An $D_{12}$-equivariant transformer for chord progression accompaniment

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-05T05:49:20.934504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 6fd7e784-5afc-4d90-bb10-f2bb2cd22e56 · outbound

This paper cites Learning transposition-invariant interval features from symbolic music and audio,.

Equivariant Music Transformer Learning transposition-invariant interval features from symbolic music and audio,

Reference 38

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 526ae2de-b37a-44c4-a4b7-b2f20ce7b121 · outbound

This paper cites Simple and controllable music generation,.

Equivariant Music Transformer Simple and controllable music generation,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:49:21.640585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 3a5a771a-a76d-4fcf-b5dd-67b2c092e004 · outbound

This paper cites Time-shifted token scheduling for symbolic music generation,.

Equivariant Music Transformer Time-shifted token scheduling for symbolic music generation,

Reference 41

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c6646503-c362-4e52-95c8-71a529bdf992 · outbound

This paper cites Learning-based methods for comparing se- quences, with applications to audio-to-midi alignment and matching,.

Equivariant Music Transformer Learning-based methods for comparing se- quences, with applications to audio-to-midi alignment and matching,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:49:21.625612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f04c6948-bd6c-4bc0-adda-3a2c831229eb · outbound

This paper cites The Llama 3 Herd of Models.

Equivariant Music Transformer The Llama 3 Herd of Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-05T05:49:20.963991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 664b2c9f-585a-4df3-b350-2da8620bd0f8 · outbound

This paper cites MIDI-LLM: Adapting large language models for text-to-MIDI mu- sic generation,.

Equivariant Music Transformer MIDI-LLM: Adapting large language models for text-to-MIDI mu- sic generation,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T05:49:21.610392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9c4c4250-0d57-4887-8d25-b4b6c50f1895 · outbound

This paper cites an unresolved cited work.

Equivariant Music Transformer Unresolved cited work

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-05T05:49:20.856972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:49:20.856972Z digest=sha256:8ab623386d41eec2a016e268a6ccb81e4b1f306e200536cdc9f7d12aadbac584

Pith citing papers

Observation 5e4c95c2-6ded-4c24-b4de-932577de86af · inbound

Equivariant Music Transformer cites this paper.

Equivariant Music Transformer Equivariant Music Transformer

Reference 1

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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