RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling | Paper Citation Record

Observation 8f88bb90-49d0-486f-a873-0e66aba0c51a · outbound

This paper cites RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling

Reference 1

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Observation 58312b56-54e5-4e56-82be-40f4aed41ed5 · outbound

This paper cites It replaces fixed bar-level boundaries with flexible rhythm-pitch primitives grouped by acoustic cues, auditory inertia, and similarity per- ception.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling It replaces fixed bar-level boundaries with flexible rhythm-pitch primitives grouped by acoustic cues, auditory inertia, and similarity per- ception

Reference 2

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Observation 8b4e8991-2eb9-49df-ab17-e01d8bbf813e · outbound

This paper cites Controlled ablations demonstrate that per- formance gains stem from perceptual grouping prin- ciples rather than model capacity.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Controlled ablations demonstrate that per- formance gains stem from perceptual grouping prin- ciples rather than model capacity

Reference 3

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RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Unresolved cited work

Reference 4

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This paper cites an unresolved cited work.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Unresolved cited work

Reference 5

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Observation fd0fbf1d-a626-493e-b983-54bbe7756305 · outbound

This paper cites HMM introduce latent states to im- plicitly control token distributions [26, 27], while dynamic Bayesian networks further explicitly model deep depen- dencies [28].

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling HMM introduce latent states to im- plicitly control token distributions [26, 27], while dynamic Bayesian networks further explicitly model deep depen- dencies [28]

Reference 6

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Observation a5d690bf-039c-49b1-9a0a-0a96ac1cef00 · outbound

This paper cites Highly accurate protein structure prediction with AlphaFold,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Highly accurate protein structure prediction with AlphaFold,

Reference 7

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RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Unresolved cited work

Reference 8

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Observation f00a6377-8042-437f-928a-3d4e368194ba · outbound

This paper cites Af- ter removing non-melody tracks and incomplete data, 274,300 melodies remain, split into train/validation/test sets at a ratio of18 : 1 : 1.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Af- ter removing non-melody tracks and incomplete data, 274,300 melodies remain, split into train/validation/test sets at a ratio of18 : 1 : 1

Reference 9

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Observation fe3500d6-515d-4433-8729-b3f8de6524ce · outbound

This paper cites Medical transformer: Gated axial-attention for medical image segmentation,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Medical transformer: Gated axial-attention for medical image segmentation,

Reference 10

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RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Unresolved cited work

Reference 11

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Observation e7b193cd-271e-47e5-8da3-d6b2b8622989 · outbound

This paper cites Experiments confirm that this frame- work significantly outperforms existing baselines in long- term structural coherence and overall musicality.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Experiments confirm that this frame- work significantly outperforms existing baselines in long- term structural coherence and overall musicality

Reference 12

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Observation be2b1d5d-16af-4f5e-b4bc-0cb0c5677904 · outbound

This paper cites A survey on deep learning for symbolic music generation: Representations, algo- rithms, evaluations, and challenges,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling A survey on deep learning for symbolic music generation: Representations, algo- rithms, evaluations, and challenges,

Reference 13

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Observation edfb7f34-a318-4f6c-9046-684958d90c43 · outbound

This paper cites Simple and control- lable music generation,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Simple and control- lable music generation,

Reference 14

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Observation 8108ebdd-85ca-4129-bd4d-f5e73ae389ab · outbound

This paper cites Wavcraft: Audio editing and generation with large language models,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Wavcraft: Audio editing and generation with large language models,

Reference 15

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This paper cites Hierarchical modeling and task decomposition: break long sequence generation into multi-level subtasks for globally controllable structure.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Hierarchical modeling and task decomposition: break long sequence generation into multi-level subtasks for globally controllable structure

Reference 16

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Observation 09755735-db25-461a-a381-ef03fee5233a · outbound

This paper cites AudioLDM: Text-to-Audio Generation with Latent Diffusion Models.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling AudioLDM: Text-to-Audio Generation with Latent Diffusion Models

Reference 17

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Observation 3eada240-9469-4c4b-864c-edb371455d99 · outbound

This paper cites Deep learning for music gen- eration: Challenges and directions,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Deep learning for music gen- eration: Challenges and directions,

Reference 18

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Observation f003d7cb-f076-40ab-a1d9-3478e9fc0721 · outbound

This paper cites Music trans- former: Generating music with long-term structure,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Music trans- former: Generating music with long-term structure,

Reference 19

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Observation 0790fc27-f1e7-4d30-bd11-d5b196eb0d17 · outbound

This paper cites Neural speech synthesis with transformer network,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Neural speech synthesis with transformer network,

Reference 20

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Observation 0809653e-a8d9-49e5-ac26-d8b88dbbde96 · outbound

This paper cites Extraction of organic chemistry grammar from unsupervised learning of chemical reac- tions,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Extraction of organic chemistry grammar from unsupervised learning of chemical reac- tions,

Reference 21

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Observation bcdbe74d-f631-4a95-bf70-f65c1b753340 · outbound

This paper cites Popmag: Pop music accompaniment generation,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Popmag: Pop music accompaniment generation,

Reference 22

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Observation 0fab26f3-1b2a-4946-89bf-0b4e818e78c4 · outbound

This paper cites Computational creativ- ity and music generation systems: An introduction to the state of the art,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Computational creativ- ity and music generation systems: An introduction to the state of the art,

Reference 23

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Observation b741c712-5c9b-4f6d-9b32-4042a5cf06a8 · outbound

This paper cites Foundation Models for Music: A Survey.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Foundation Models for Music: A Survey

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Observation 02738301-8d01-417d-ba26-5f6255f9abf7 · outbound

This paper cites Deep learning’s shallow gains: A comparative evaluation of algorithms for automatic music generation,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Deep learning’s shallow gains: A comparative evaluation of algorithms for automatic music generation,

Reference 25

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Observation 58e48f71-9975-4373-ad90-759703e75bcc · outbound

This paper cites Bader,Springer Handbook of Systematic Musicol- ogy.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Bader,Springer Handbook of Systematic Musicol- ogy

Reference 26

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Observation 0967be33-e259-4755-96dd-4530744bdc3b · outbound

This paper cites Museformer: Transformer with fine-and coarse-grained attention for music genera- tion,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Museformer: Transformer with fine-and coarse-grained attention for music genera- tion,

Reference 27

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Observation 5eb9305b-26b4-44eb-ba98-316ae17ffa8c · outbound

This paper cites Theme transformer: Symbolic music genera- tion with theme-conditioned transformer,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Theme transformer: Symbolic music genera- tion with theme-conditioned transformer,

Reference 28

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Observation 810cfd85-1f0e-4eb7-8195-cd0cb5a5dda2 · outbound

This paper cites Melons: Generating melody with long-term structure using transformers and structure graph,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Melons: Generating melody with long-term structure using transformers and structure graph,

Reference 29

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Observation e3ecbf64-8c57-4a08-971b-25ba839768d2 · outbound

This paper cites PopMNet: Gener- ating structured pop music melodies using neural net- works,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling PopMNet: Gener- ating structured pop music melodies using neural net- works,

Reference 30

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RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Unresolved cited work

Reference 31

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Observation 3d359d16-e375-444b-be71-3179e8522228 · outbound

This paper cites Grouping conditions in listening to music: An approach to Lerdahl & Jackendoff’s grouping pref- erence rules,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Grouping conditions in listening to music: An approach to Lerdahl & Jackendoff’s grouping pref- erence rules,

Reference 32

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Observation 01871328-bbb3-49c3-9855-fec14e6f5d59 · outbound

This paper cites Motivic structure and the perception of similarity,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Motivic structure and the perception of similarity,

Reference 33

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Observation 387e7434-6fae-43bd-bafa-645b99369b68 · outbound

This paper cites Attention is all you need,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Attention is all you need,

Reference 34

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Observation 08900c7c-8525-4b09-9ad5-9210ec09f895 · outbound

This paper cites Interval and contour in melody process- ing,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Interval and contour in melody process- ing,

Reference 35

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Observation ece6df22-cab7-43e5-bdf9-bb8fd5a75a5b · outbound

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RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Pitch and contour in music processing

Reference 36

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Observation 262c2a9e-f1d6-4e66-9749-246814a34b95 · outbound

This paper cites An experiment in musical composition,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling An experiment in musical composition,

Reference 37

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Observation 3b60551e-df7f-441e-ada7-26336296f1be · outbound

This paper cites A hidden Markov model of melody production in Greek church chant,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling A hidden Markov model of melody production in Greek church chant,

Reference 38

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Observation 7458c5d1-a5f6-4198-84b8-04f2528a3118 · outbound

This paper cites HMM Analysis of Musical Structure: Identifi- cation of Latent Variables Through Topology-Sensitive Model Selection,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling HMM Analysis of Musical Structure: Identifi- cation of Latent Variables Through Topology-Sensitive Model Selection,

Reference 39

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RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Unresolved cited work

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Observation 5243d8bb-9374-4893-83f3-eb8c863fcab7 · outbound

This paper cites Song From PI: A Musically Plausible Network for Pop Music Gen- eration,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Song From PI: A Musically Plausible Network for Pop Music Gen- eration,

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Observation c6ae8130-2dc2-4f99-b4c0-c760ca933878 · outbound

This paper cites A Hi- erarchical Latent Variable Encoder-Decoder Model for Generating Dialogues,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling A Hi- erarchical Latent Variable Encoder-Decoder Model for Generating Dialogues,

Reference 42

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This paper cites MidiNet: A Convolutional Generative Adversarial Network for Symbolic-Domain Music Generation,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling MidiNet: A Convolutional Generative Adversarial Network for Symbolic-Domain Music Generation,

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Observation 714b857d-4ee8-425f-90a6-d251ecf7e61a · outbound

This paper cites Transformer-xl: Attentive language models beyond a fixed-length context,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Transformer-xl: Attentive language models beyond a fixed-length context,

Reference 44

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Observation 001aeb85-cd84-4f5b-8c4b-27c991fd0785 · outbound

This paper cites Transformers are rnns: Fast autoregressive transform- ers with linear attention,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Transformers are rnns: Fast autoregressive transform- ers with linear attention,

Reference 45

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Observation b4b20070-c84e-452d-9d8a-0a72736a4fd1 · outbound

This paper cites Lerdahl and R.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Lerdahl and R

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Observation 78d014b9-90f2-4265-84ea-b851b49ea615 · outbound

This paper cites miditok: A Python package for MIDI file tokenization.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling miditok: A Python package for MIDI file tokenization

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Observation b2df3f41-7de9-4470-aea2-bc36d4cfe8a3 · outbound

This paper cites PhraseV AE and PhraseLDM: La- tent Diffusion for Full-Song Multitrack Symbolic Mu- sic Generation,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling PhraseV AE and PhraseLDM: La- tent Diffusion for Full-Song Multitrack Symbolic Mu- sic Generation,

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Observation 1a57530f-8947-42c9-a8ce-4c1e10339fd9 · outbound

This paper cites PhraseLDM [36] is excluded due to its re- liance on explicit phrase annotations unavailable in Melo- dyNet.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling PhraseLDM [36] is excluded due to its re- liance on explicit phrase annotations unavailable in Melo- dyNet

Reference 49

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This paper cites Byte pair encoding for symbolic music,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Byte pair encoding for symbolic music,

Reference 50

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Observation 0d75b469-e123-409e-8c21-b912b956735d · outbound

This paper cites The Jazz Transformer on the Front Line: Exploring the Shortcomings of AI- composed Music through Quantitative Measures,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling The Jazz Transformer on the Front Line: Exploring the Shortcomings of AI- composed Music through Quantitative Measures,

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Observation be998178-f485-48e2-95e6-af29c9325543 · outbound

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

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Musicbert: Symbolic music understanding with large- scale pre-training,

Reference 52

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Observation aa2b0fac-9cc6-4e19-b4ac-0384a2397043 · outbound

This paper cites Structure-enhanced pop music generation via harmony-aware learning,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Structure-enhanced pop music generation via harmony-aware learning,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-01T11:48:12.826778Z

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Observation cc4be4ba-81b4-4432-93ec-14891597435f · outbound

This paper cites The power of fragmen- tation: A hierarchical transformer model for struc- tural segmentation in symbolic music generation,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling The power of fragmen- tation: A hierarchical transformer model for struc- tural segmentation in symbolic music generation,

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-01T11:48:12.901179Z

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Observation dde513be-67f5-4b0a-975f-33309430db2e · outbound

This paper cites Controllable deep melody generation via hierarchi- cal music structure representation,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Controllable deep melody generation via hierarchi- cal music structure representation,

Reference 55

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Observation ef07ab24-b5c1-4f61-be83-f6b0d5116104 · outbound

This paper cites A theme music genera- tion model based on hybrid variational autoencoders and conditional generative adversarial networks,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling A theme music genera- tion model based on hybrid variational autoencoders and conditional generative adversarial networks,

Reference 56

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This paper cites Introduction to Schenke- rian analysis,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Introduction to Schenke- rian analysis,

Reference 57

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Observation 28f84b93-0abd-4d5d-a7b7-060f97c15b74 · outbound

This paper cites Processing of hierarchical syntactic structure in music,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Processing of hierarchical syntactic structure in music,

Reference 58

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This paper cites Implicit learning and acquisition of music,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Implicit learning and acquisition of music,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-01T11:48:13.438901Z

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Observation 7e1d3521-41e4-4479-8f74-366b1c19a9b0 · outbound

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

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Compound word transformer: Learning to compose full-song music over dynamic directed hypergraphs,

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-01T11:48:13.530103Z

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Observation 161a8d75-1753-4b61-911a-a6519401ad35 · outbound

This paper cites MelodyGLM: Multi-task Pre-training for Symbolic Melody Generation.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling MelodyGLM: Multi-task Pre-training for Symbolic Melody Generation

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-01T11:48:13.588241Z

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Observation 10f711a5-1e87-44b8-8e32-df7574d8f23a · outbound

This paper cites Survey on the evaluation of generative models in music,.

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling Survey on the evaluation of generative models in music,

Reference 62

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