Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction | Paper Citation Record

Observation 01bec87a-61f1-47f4-9840-566da279497d · outbound

This paper cites Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction

Reference 1

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Observation b9189ced-21c9-4f55-b043-b3f619950f8a · outbound

This paper cites Each note contains at least three attributes: onset timing, note duration, and note pitch.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Each note contains at least three attributes: onset timing, note duration, and note pitch

Reference 2

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Observation a901f250-9fd9-4ca3-9cd0-1b31d0cdd201 · outbound

This paper cites the pitch difference between E4 and C4 is necessarily a major third.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction the pitch difference between E4 and C4 is necessarily a major third

Reference 3

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This paper cites We refer to the combination of all these tasks and datasets as the SMC benchmark, which stands for Symbolic Music Classifica- tion benchmark.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction We refer to the combination of all these tasks and datasets as the SMC benchmark, which stands for Symbolic Music Classifica- tion benchmark

Reference 4

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This paper cites no label.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction no label

Reference 5

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This paper cites The cor- ruption hyperparameters r pos, r pit, and r dur are set to 4, 12, and 12, respectively.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction The cor- ruption hyperparameters r pos, r pit, and r dur are set to 4, 12, and 12, respectively

Reference 6

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This paper cites For reference, we show the state-of-the-art (SOTA) performance of the tasks in the last row, if available.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction For reference, we show the state-of-the-art (SOTA) performance of the tasks in the last row, if available

Reference 7

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Observation 7374f726-97af-4754-a3fa-8d81bdbe7984 · outbound

This paper cites an unresolved cited work.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Unresolved cited work

Reference 8

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This paper cites an unresolved cited work.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Unresolved cited work

Reference 9

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This paper cites an unresolved cited work.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Unresolved cited work

Reference 10

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Observation 5c4dfcc5-1fbd-4d99-b2b0-97e01df861cd · outbound

This paper cites BERT-like Pre-training for Symbolic Piano Music Classification Tasks.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction BERT-like Pre-training for Symbolic Piano Music Classification Tasks

Reference 11

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Observation 17acdb3f-2132-474b-af21-e039fa656199 · outbound

This paper cites PianoBART: Symbolic piano mu- sic generation and understanding with large-scale pre- training,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction PianoBART: Symbolic piano mu- sic generation and understanding with large-scale pre- training,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:27.185324Z

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Observation de87e1d7-92d7-4b94-a3c6-6e8158007a14 · outbound

This paper cites Let Network Decide What to Learn: Symbolic Music Understanding Model Based on Large-scale Adversarial Pre-training.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Let Network Decide What to Learn: Symbolic Music Understanding Model Based on Large-scale Adversarial Pre-training

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:44:26.696549Z

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This paper cites More than simply masking: Exploring pre-training strategies for symbolic music understanding,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction More than simply masking: Exploring pre-training strategies for symbolic music understanding,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:27.177974Z

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Observation 4fbb0cdb-f734-4ff4-bd24-5882d0daf1db · outbound

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

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction MusicBERT: Symbolic music understanding with large-scale pre-training,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:27.170242Z

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Observation 3657cf15-3e5c-4898-8937-d0774f8450ce · outbound

This paper cites MuseBERT: Pre-training mu- sic representation for music understanding and control- lable generation,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction MuseBERT: Pre-training mu- sic representation for music understanding and control- lable generation,

Reference 16

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Observation a44bd3ac-5cc2-40ca-b3e0-cab272b60b3a · outbound

This paper cites RNBert: Fine-tuning a masked language model for roman numeral analysis,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction RNBert: Fine-tuning a masked language model for roman numeral analysis,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:27.155129Z

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Observation b2edb84e-07f1-4129-9569-770dbb9f09a6 · outbound

This paper cites GPT-4 Technical Report.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction GPT-4 Technical Report

Reference 18

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This paper cites LLaMA: Open and Efficient Foundation Language Models.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction LLaMA: Open and Efficient Foundation Language Models

Reference 19

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This paper cites Open LLM leaderboard,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Open LLM leaderboard,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:27.147471Z

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Observation f05d9d1e-9d85-4a6d-934f-85aa0f734738 · outbound

This paper cites BERT: pre-training of deep bidirectional transform- ers for language understanding,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction BERT: pre-training of deep bidirectional transform- ers for language understanding,

Reference 21

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Observation ca3eeea4-9d21-433c-bdb0-6f33ee895b1a · outbound

This paper cites Melodic matching techniques for large music databases,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Melodic matching techniques for large music databases,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:27.132502Z

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Observation 245bf3e6-a90b-4918-863d-c3b3e8afffb0 · outbound

This paper cites A convolutional approach to melody line identification in symbolic scores,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction A convolutional approach to melody line identification in symbolic scores,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:27.125063Z

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Observation 406522a3-a61c-49d4-93e7-a0ba64eab3af · outbound

This paper cites A deep learning method for melody extraction from a polyphonic symbolic music representation,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction A deep learning method for melody extraction from a polyphonic symbolic music representation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:27.117313Z

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This paper cites Augment- edNet: A roman numeral analysis network with syn- thetic training examples and additional tonal tasks,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Augment- edNet: A roman numeral analysis network with syn- thetic training examples and additional tonal tasks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:27.109435Z

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This paper cites Roman numeral anal- ysis with graph neural networks: Onset-wise predic- tions from note-wise features,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Roman numeral anal- ysis with graph neural networks: Onset-wise predic- tions from note-wise features,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:27.101664Z

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Observation 1d53fb6c-5db4-4dea-adca-37d9a4cdedd2 · outbound

This paper cites Natural Language Processing Methods for Symbolic Music Generation and Information Retrieval: a Survey.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Natural Language Processing Methods for Symbolic Music Generation and Information Retrieval: a Survey

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:44:26.668417Z

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This paper cites Bps-motif: A dataset for repeated pattern discovery of polyphonic symbolic music,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Bps-motif: A dataset for repeated pattern discovery of polyphonic symbolic music,

Reference 28

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This paper cites 2013:Discovery of Repeated Themes & Sections,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction 2013:Discovery of Repeated Themes & Sections,

Reference 29

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This paper cites Algo- rithms for discovering repeated patterns in multidimen- sional representations of polyphonic music,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Algo- rithms for discovering repeated patterns in multidimen- sional representations of polyphonic music,

Reference 30

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This paper cites Functional harmony recogni- tion of symbolic music data with multi-task recurrent neural networks,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Functional harmony recogni- tion of symbolic music data with multi-task recurrent neural networks,

Reference 31

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This paper cites S3: A symbolic music dataset for computational music analysis of symphonies,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction S3: A symbolic music dataset for computational music analysis of symphonies,

Reference 32

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This paper cites Improving genre annotations for the million song dataset,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Improving genre annotations for the million song dataset,

Reference 33

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This paper cites Symbolic Music Structure Analysis with Graph Representations and Changepoint Detection Methods.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Symbolic Music Structure Analysis with Graph Representations and Changepoint Detection Methods

Reference 34

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

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction EMOPIA: A multi-modal pop piano dataset for emotion recognition and emotion-based music gen- eration,

Reference 35

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This paper cites Multimodal multifaceted music emotion recognition based on self-attentive fusion of psychology-inspired symbolic and acoustic features,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Multimodal multifaceted music emotion recognition based on self-attentive fusion of psychology-inspired symbolic and acoustic features,

Reference 36

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This paper cites ASAP: a dataset of aligned scores and per- formances for piano transcription,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction ASAP: a dataset of aligned scores and per- formances for piano transcription,

Reference 37

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This paper cites ATEPP: A dataset of automat- ically transcribed expressive piano performance,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction ATEPP: A dataset of automat- ically transcribed expressive piano performance,

Reference 38

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This paper cites A-MAPS: Augmented MAPS dataset with rhythm and key annotations,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction A-MAPS: Augmented MAPS dataset with rhythm and key annotations,

Reference 39

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This paper cites Can LLMs.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Can LLMs

Reference 40

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This paper cites ChatMusician: Understanding and generating music intrinsically with LLM,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction ChatMusician: Understanding and generating music intrinsically with LLM,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.999975Z

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This paper cites On the Opportunities and Risks of Foundation Models.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction On the Opportunities and Risks of Foundation Models

Reference 42

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This paper cites A foundation model for music informatics,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction A foundation model for music informatics,

Reference 43

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Observation ce730e4c-d9b2-434d-addf-a1510ce7991c · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Learning transferable visual models from natural language supervision,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.984522Z

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This paper cites SUPERB: speech processing universal performance benchmark,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction SUPERB: speech processing universal performance benchmark,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.977157Z

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This paper cites WavLM: Large-scale self-supervised pre-training for full stack speech processing,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction WavLM: Large-scale self-supervised pre-training for full stack speech processing,

Reference 46

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This paper cites Dynamic-SUPERB Phase-2: A collaboratively expanding benchmark for measuring the capabilities of spoken language models with 180 tasks,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Dynamic-SUPERB Phase-2: A collaboratively expanding benchmark for measuring the capabilities of spoken language models with 180 tasks,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.961669Z

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This paper cites MERT: acoustic music understanding model with large-scale self-supervised training,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction MERT: acoustic music understanding model with large-scale self-supervised training,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.954052Z

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Observation c555235f-cb26-4e99-b858-18b54cf2a7c6 · outbound

This paper cites Music Foundation Model as Generic Booster for Music Downstream Tasks.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Music Foundation Model as Generic Booster for Music Downstream Tasks

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:44:26.635177Z

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 82a12ecd-cbba-43e4-afcc-f52055c1908f · outbound

This paper cites Codified au- dio language modeling learns useful representations for music information retrieval,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Codified au- dio language modeling learns useful representations for music information retrieval,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.946378Z

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 41ef8ee5-3074-47c9-a9ba-d28b7c5e9e32 · outbound

This paper cites MelodyT5: A unified score-to-score transformer for symbolic mu- sic processing,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction MelodyT5: A unified score-to-score transformer for symbolic mu- sic processing,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.938797Z

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 ef15f31c-fffc-4cda-8a91-72240e912fda · outbound

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

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Compound word transformer: Learning to compose full-song mu- sic over dynamic directed hypergraphs,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.930971Z

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 16e5bd00-9d9d-48be-840d-37e24dbfade2 · outbound

This paper cites Attention is all you need,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Attention is all you need,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.922625Z

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 ea19e7ff-3e42-4652-8877-abce79d33bee · outbound

This paper cites Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T19:44:26.197256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e445c5f-97cd-4b2e-8ed0-0182b8fc70c9 · outbound

This paper cites FlashAttention: fast and memory-efficient exact at- tention with IO-awareness,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction FlashAttention: fast and memory-efficient exact at- tention with IO-awareness,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.914408Z

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 8068973b-255f-47cb-8a73-1d88091be08e · outbound

This paper cites Roformer: Enhanced transformer with ro- tary position embedding,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Roformer: Enhanced transformer with ro- tary position embedding,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.906508Z

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 1b61818f-7b07-401a-93e0-923df8a59c1b · outbound

This paper cites Representation deficiency in masked language modeling,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Representation deficiency in masked language modeling,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.898188Z

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 14829d09-62c9-4184-abdb-e4808f0c80a9 · outbound

This paper cites Perfor- mance midi-to-score conversion by neural beat track- ing,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Perfor- mance midi-to-score conversion by neural beat track- ing,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.890268Z

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 60c686f0-fbab-4caf-be2c-5fdfe584674e · outbound

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

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction POP909: A pop-song dataset for mu- sic arrangement generation,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.881539Z

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 0a7787a2-64f7-46ed-941a-167756ffce76 · outbound

This paper cites A cor- pus describing orchestral texture in first movements of classical and early-romantic symphonies,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction A cor- pus describing orchestral texture in first movements of classical and early-romantic symphonies,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.872908Z

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 7c2a2cd4-12ea-4a1f-a1c6-778bf250afdf · outbound

This paper cites Orchestral texture classification with convolution,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Orchestral texture classification with convolution,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.863995Z

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 9e4e0e86-08c8-4ebb-9461-282eb62173ea · outbound

This paper cites Position- ing left-hand movement in violin performance: A sys- tem and user study of fingering pattern generation,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Position- ing left-hand movement in violin performance: A sys- tem and user study of fingering pattern generation,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.855770Z

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 91287002-46b7-4be5-a627-280f8297cab2 · outbound

This paper cites Enhancing violin fin- gering generation through audio-symbolic fusion,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Enhancing violin fin- gering generation through audio-symbolic fusion,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.847249Z

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 c9575096-3ada-43bc-8ffb-8ae938ca9898 · outbound

This paper cites Stable and low- precision training for large-scale vision-language mod- els,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Stable and low- precision training for large-scale vision-language mod- els,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.838672Z

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 86374b35-4ef3-4957-9cc5-f501761a1b55 · outbound

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

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Learning-based methods for comparing se- quences, with applications to audio-to-midi alignment and matching,

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-06T19:44:26.569631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dbd492f-3151-484f-8570-d08e8ec5e528 · outbound

This paper cites Multi-mmlg: a novel framework of ex- tracting multiple main melodies from MIDI files,.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Multi-mmlg: a novel framework of ex- tracting multiple main melodies from MIDI files,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:44:26.825176Z

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 caba295d-f5dd-437e-a5e2-211db8f0e0e2 · outbound

This paper cites The Llama 3 Herd of Models.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction The Llama 3 Herd of Models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T19:44:26.574543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ada80e16-e6b6-42e4-9f4d-01a21d611cf9 · outbound

This paper cites Deep Learning Scaling is Predictable, Empirically.

Improving BERT for Symbolic Music Understanding Using Token Denoising and Pianoroll Prediction Deep Learning Scaling is Predictable, Empirically

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-06T19:44:26.577506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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