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Paper Citation Record · LEDGER

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music

As of 10 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 2 inbound Pith citation observations for arXiv:2607.10003.

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

pith.paper-citation-record.v1
2607.10003 v1

Coverage vector

measured 34 of 34 reference resolution

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measured 36 of 36 standing notices

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:42:37.123392Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T18:42:37.302502Z

Reference resolution

34 of 34 outbound references displayed

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Outbound references

Observation bd62f60e-1d5c-4bf2-b2a4-11864be8eff5 · outbound

This paper cites ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music

Reference 1

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Observation 997163c6-0e09-4186-9473-eacd6fb60513 · outbound

This paper cites We therefore re- view each area.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music We therefore re- view each area

Reference 2

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Observation 03169d3f-39dc-4c89-b739-fab33cf15d4f · outbound

This paper cites We in- troduce the input representation, model components, and training objectives in the specification below.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music We in- troduce the input representation, model components, and training objectives in the specification below

Reference 3

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Observation 9ee83284-407e-4464-b255-4f899af77c97 · outbound

This paper cites Both used= 512, 8 heads, and an FFN dimension of 2048.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Both used= 512, 8 heads, and an FFN dimension of 2048

Reference 4

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Observation 92cb8939-f080-4b48-a442-f3cd2657b26f · outbound

This paper cites next-window.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music next-window

Reference 5

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Observation f888acf2-76bc-4a8c-99dc-45839974d26e · outbound

This paper cites an unresolved cited work.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Unresolved cited work

Reference 6

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Observation 2fdecc3c-fc52-475f-8577-39b7dce74a77 · outbound

This paper cites All scientific decisions, experimental de- signs, figure drawing, results analysis and discussion were completely made by humans.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music All scientific decisions, experimental de- signs, figure drawing, results analysis and discussion were completely made by humans

Reference 7

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Observation 002c5c51-68a8-4626-b96b-9a92f0f32e6f · outbound

This paper cites MidiBERT-Piano: Large-scale pre-training for symbolic music classification tasks,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music MidiBERT-Piano: Large-scale pre-training for symbolic music classification tasks,

Reference 8

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Observation 869a5a54-dd3b-4695-9dc8-5fc57af0974a · outbound

This paper cites MusicBERT: Symbolic music understanding with large-scale pre-training,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music MusicBERT: Symbolic music understanding with large-scale pre-training,

Reference 9

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Observation 72002ffe-16b1-4e5d-8905-9afd70f91a54 · outbound

This paper cites PianoBART: Symbolic piano music genera- tion and understanding with large-scale pre-training,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music PianoBART: Symbolic piano music genera- tion and understanding with large-scale pre-training,

Reference 10

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Observation a3952141-2f62-4abf-a961-4b3349c6c31b · outbound

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

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Scaling self-supervised representation learning for symbolic piano performance,

Reference 11

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Observation 6e1018a0-180e-4686-ad4f-4b06eaae35d0 · outbound

This paper cites Natural language processing methods for symbolic music generation and information retrieval: A survey,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Natural language processing methods for symbolic music generation and information retrieval: A survey,

Reference 12

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Observation c6a72841-3c33-408b-a4a8-0bc79cfb5c9a · outbound

This paper cites Pop music transformer: Beat-based modeling and generation of expressive pop piano compositions,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Pop music transformer: Beat-based modeling and generation of expressive pop piano compositions,

Reference 13

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Observation 99bea12f-a643-489e-8a28-6211e36479bc · outbound

This paper cites Compound word transformer: Learning to compose full-song music over dynamic directed hypergraphs,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Compound word transformer: Learning to compose full-song music over dynamic directed hypergraphs,

Reference 14

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Observation 537f7179-3b0b-4971-93ce-f5c6665cb521 · outbound

This paper cites Clamp: Contrastive language-music pre-training for cross- modal symbolic music information retrieval,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Clamp: Contrastive language-music pre-training for cross- modal symbolic music information retrieval,

Reference 15

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Observation 0eb11ace-4128-4970-be30-dad4c2e0d3cd · outbound

This paper cites Self-supervised learning from images with a joint- embedding predictive architecture,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Self-supervised learning from images with a joint- embedding predictive architecture,

Reference 16

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Observation daad2de4-2f19-4360-b1cd-307e857762d5 · outbound

This paper cites Revisiting Feature Prediction for Learning Visual Representations from Video.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Revisiting Feature Prediction for Learning Visual Representations from Video

Reference 17

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Observation 610a817f-c4c9-43b4-ac82-94e4b4b4af1c · outbound

This paper cites LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels

Reference 18

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Observation da2f0a1c-cfc7-437d-85f3-371657b2f5fa · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Representation Learning with Contrastive Predictive Coding

Reference 19

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Observation 0160171b-2191-4ec7-9848-0223962fa8ac · outbound

This paper cites Improving BERT for symbolic music understanding using token denoising and pi- anoroll prediction,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Improving BERT for symbolic music understanding using token denoising and pi- anoroll prediction,

Reference 20

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Observation bfd433a0-e245-4c0a-870e-0319a7f843a2 · outbound

This paper cites Attention is all you need,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Attention is all you need,

Reference 21

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Observation 454124a5-1911-4e5d-985b-3eb7f7d282b8 · outbound

This paper cites Bootstrap your own la- tent – a new approach to self-supervised learning,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Bootstrap your own la- tent – a new approach to self-supervised learning,

Reference 22

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Observation 459e1e01-8ee8-4e67-a7f6-ee6d822d3b9a · outbound

This paper cites High- resolution piano transcription with pedals by regress- ing onset and offset times,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music High- resolution piano transcription with pedals by regress- ing onset and offset times,

Reference 23

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Observation 80a06ca2-9a22-4a6b-a44e-dea432f35661 · outbound

This paper cites Deep networks with stochastic depth,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Deep networks with stochastic depth,

Reference 24

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Observation 94ff1960-d9f6-4a0f-9ac7-f8d913ec43a6 · outbound

This paper cites ATEPP: A dataset of automatically tran- scribed expressive piano performance,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music ATEPP: A dataset of automatically tran- scribed expressive piano performance,

Reference 25

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Observation 898c1c9e-4049-4734-8ff3-589297a731c4 · outbound

This paper cites POP909: A pop-song dataset for music arrangement generation,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music POP909: A pop-song dataset for music arrangement generation,

Reference 26

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Observation 8e694ea8-7282-4ce0-b219-d1069cc2f3e4 · outbound

This paper cites EMOPIA: A multi-modal pop piano dataset for emotion recognition and emotion-based music gen- eration,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music EMOPIA: A multi-modal pop piano dataset for emotion recognition and emotion-based music gen- eration,

Reference 27

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Observation 6ec27226-f024-4792-a299-fbf48c5b23a2 · outbound

This paper cites Decoupled weight decay regularization,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Decoupled weight decay regularization,

Reference 28

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Observation 87427eef-93e6-4765-911d-7a7c6ba58f8f · outbound

This paper cites Pianist8 dataset,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Pianist8 dataset,

Reference 29

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Observation 6cc304ea-5d01-4af3-b51a-38622151636b · outbound

This paper cites Bachi: Boundary-aware symbolic chord recognition through masked iterative decoding on pop and classi- cal music,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Bachi: Boundary-aware symbolic chord recognition through masked iterative decoding on pop and classi- cal music,

Reference 30

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Observation 7cd2e891-63df-45d0-8a86-86154d48ec39 · outbound

This paper cites Combining piano perfor- mance dimensions for score difficulty classification,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Combining piano perfor- mance dimensions for score difficulty classification,

Reference 31

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Observation bd64dd76-50f2-49c3-957a-025361ca4c29 · outbound

This paper cites ASAP: A dataset of aligned scores and performances for piano transcription,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music ASAP: A dataset of aligned scores and performances for piano transcription,

Reference 32

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Observation 2ca21946-69f1-424b-b8af-a96f6a04d7b2 · outbound

This paper cites VICReg: Variance-invariance-covariance regularization for self- supervised learning,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music VICReg: Variance-invariance-covariance regularization for self- supervised learning,

Reference 33

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Observation 73e8eb01-b4cc-46b8-9501-d867f8e3f320 · outbound

This paper cites Learning from reward-free offline data: A case for planning with latent dynamics mod- els,.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music Learning from reward-free offline data: A case for planning with latent dynamics mod- els,

Reference 34

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Pith citing papers

Observation bd62f60e-1d5c-4bf2-b2a4-11864be8eff5 · inbound

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music cites this paper.

ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music

Reference 1

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Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation cites this paper.

Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music

Reference 42

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-08T18:42:37.123392Z digest=sha256:a097b96e5203de2d006835db12681949dd4b7d23ed2cf5773d1856ae0f51575d