Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T18:42:37.133267Z
Paper Citation Record · LEDGER
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation
As of 10 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2608.04378.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
45 of 45 outbound references displayed
- verified exact4
- verified fuzzy25
- unresolved15
- parse uncertain1
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 0a8874bf-1f7d-4649-9a84-57fa7402b568 · outbound
This paper cites Self-supervised learning from images with a joint- embedding predictive architecture.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Self-supervised learning from images with a joint- embedding predictive architecture
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:38.080911Z
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.
Observation 87ab2416-fe04-4adf-a606-c7d2920dc467 · outbound
This paper cites LeJEPA: Provable and scalable self-supervised learning without the heuristics, 2025.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation LeJEPA: Provable and scalable self-supervised learning without the heuristics, 2025
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:38.063959Z
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.
Observation f0ce2832-a2bc-4771-a2d8-30745e4a1e7d · outbound
This paper cites Bittner, Juan José Bosch, David Rubinstein, Gabriel Meseguer-Brocal, and Sebastian Ewert.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Bittner, Juan José Bosch, David Rubinstein, Gabriel Meseguer-Brocal, and Sebastian Ewert
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:38.048869Z
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.
Observation 2cf73a05-3977-49d2-80f3-fc2571c3f015 · outbound
This paper cites Zapata, and Xavier Serra.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Zapata, and Xavier Serra
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:38.032439Z
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.
Observation 8ab0eeaf-e0d4-4b3c-90ec-aca0412ce320 · outbound
This paper cites Emerging properties in self-supervised vision transformers.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Emerging properties in self-supervised vision transformers
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:38.017269Z
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.
Observation 59777f34-56c3-4d60-b615-a86b8be63621 · outbound
This paper cites Codified audio language modeling learns useful representations for music information retrieval.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Codified audio language modeling learns useful representations for music information retrieval
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:38.001701Z
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.
Observation 5c3baffb-2a94-4a1e-8893-96df08d80ae6 · outbound
This paper cites Music SketchNet: Controllable Music Generation via Factorized Representations of Pitch and Rhythm.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Music SketchNet: Controllable Music Generation via Factorized Representations of Pitch and Rhythm
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T18:42:37.568953Z
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.
Observation 8b25a6df-49bf-4ad7-9374-fec2b95402df · outbound
This paper cites Pixelflow: Pixel-space generative models with flow, 2025.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Pixelflow: Pixel-space generative models with flow, 2025
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:42:36.950691Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b76b3215-d6ea-4ee0-a166-f468f897a65c · outbound
This paper cites Automatic Analysis and Influence of Hierarchical Structure on Melody, Rhythm and Harmony in Popular Music.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Automatic Analysis and Influence of Hierarchical Structure on Melody, Rhythm and Harmony in Popular Music
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:42:36.955570Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0872e412-f945-466a-b80e-e54c31e0fc54 · outbound
This paper cites Diffusion models beat GANs on image synthesis.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Diffusion models beat GANs on image synthesis
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.976481Z
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.
Observation 99673cb7-a190-4952-9601-3eaf6166e80b · outbound
This paper cites Generative modelling in latent space, 2025.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Generative modelling in latent space, 2025
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.962049Z
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.
Observation ee53d3be-8918-411f-a66a-0973ca62549c · outbound
This paper cites Hawley, and Jordi Pons.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Hawley, and Jordi Pons
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.946586Z
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.
Observation ec1dd9e5-264d-4417-b06f-3f8a9553fca9 · outbound
This paper cites Learning and Leveraging World Models in Visual Representation Learning.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Learning and Leveraging World Models in Visual Representation Learning
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:42:36.975241Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 823ffb86-9a19-46ce-8fac-aed9cf3d4be2 · outbound
This paper cites World Models.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation World Models
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:42:36.980422Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19e4507f-3ca4-4b83-985a-1df8eaaef8b7 · outbound
This paper cites Using a joint-embedding predictive architecture for symbolic music understanding.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Using a joint-embedding predictive architecture for symbolic music understanding
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.929987Z
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.
Observation 2a4bf12f-9026-413b-a7da-0e8174363d51 · outbound
This paper cites an unresolved cited work.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T18:42:37.914256Z
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.
Observation dcf967d7-5d7b-4c45-9c3f-0b29962cccbf · outbound
This paper cites an unresolved cited work.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T18:42:37.898382Z
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.
Observation 58bff056-ca19-4e5f-94e5-a646e70108bd · outbound
This paper cites EMOPIA: A multi-modal pop piano dataset for emotion recognition and emotion-based music generation.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation EMOPIA: A multi-modal pop piano dataset for emotion recognition and emotion-based music generation
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.882781Z
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.
Observation 776a0ebf-080a-4d0b-bcc9-900b302cffdc · outbound
This paper cites How far can pretrained LLMs go in symbolic music? controlled comparisons of supervised and preference- based adaptation.arXiv preprint arXiv:2601.22764, 2026.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation How far can pretrained LLMs go in symbolic music? controlled comparisons of supervised and preference- based adaptation.arXiv preprint arXiv:2601.22764, 2026
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:42:37.005741Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cb009084-0471-46a6-918f-b6819232b411 · outbound
This paper cites A path towards autonomous machine intelligence.OpenReview preprint, 2022.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation A path towards autonomous machine intelligence.OpenReview preprint, 2022
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.867340Z
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.
Observation df7df0f6-71f8-4b7f-92f3-da69e35974af · outbound
This paper cites an unresolved cited work.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Unresolved cited work
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:42:37.015774Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ed68fb50-386a-41f0-9356-2fe0385ab834 · outbound
This paper cites Swin transformer V2: Scaling up capacity and resolution.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Swin transformer V2: Scaling up capacity and resolution
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.841633Z
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.
Observation 23e7dc7b-507c-4dab-86b3-6699f2f59d6f · outbound
This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Swin transformer: Hierarchical vision transformer using shifted windows
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.826192Z
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.
Observation f4fec9ca-7df3-44f8-9754-a72c49232f45 · outbound
This paper cites One-step latent-free image generation with pixel mean flows, 2026.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation One-step latent-free image generation with pixel mean flows, 2026
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.809553Z
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.
Observation 2d36acc3-76b4-4d96-a9b7-a0d8875d630b · outbound
This paper cites CMI-Bench: A comprehensive benchmark for evaluating music instruction following.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation CMI-Bench: A comprehensive benchmark for evaluating music instruction following
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.794140Z
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.
Observation 75e79708-a7b9-4776-8996-3be58b18a4d3 · outbound
This paper cites Pnp-flow: Plug-and-play image restoration with flow matching.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Pnp-flow: Plug-and-play image restoration with flow matching
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.778168Z
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.
Observation 85c8f97e-4f54-4634-8f48-c8cedf74184f · outbound
This paper cites an unresolved cited work.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Unresolved cited work
Reference 27
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T18:42:37.762821Z
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.
Observation 134e1ddc-edaa-47a2-b3c8-48fd902bb68c · outbound
This paper cites Polyffusion: A diffusion model for polyphonic score generation with internal and external controls.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Polyffusion: A diffusion model for polyphonic score generation with internal and external controls
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.747648Z
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.
Observation c8146f13-b4f8-4ba4-a32e-9f4b3cf33c60 · outbound
This paper cites DINOv2: Learning Robust Visual Features without Supervision.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation DINOv2: Learning Robust Visual Features without Supervision
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:42:37.055751Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cc2dee26-7156-484b-99a7-ad1273520a00 · outbound
This paper cites Muckley, Ricky T.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Muckley, Ricky T
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:42:37.060824Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 40c9a460-054b-4def-828c-bc6a56b1a33e · outbound
This paper cites PhD thesis, Columbia University, 2016.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation PhD thesis, Columbia University, 2016
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.720976Z
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.
Observation 223d6f9e-ba15-4769-9dcd-69218455e90f · outbound
This paper cites Stem- JEPA: A joint-embedding predictive architecture for musical stem compatibility estimation.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Stem- JEPA: A joint-embedding predictive architecture for musical stem compatibility estimation
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.703918Z
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.
Observation 0f15c106-a328-41bd-89bd-081b0e7f38c1 · outbound
This paper cites Crash: Raw audio score-based generative modeling for controllable high-resolution drum sound synthesis, 2021.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Crash: Raw audio score-based generative modeling for controllable high-resolution drum sound synthesis, 2021
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.688676Z
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.
Observation 6bb44a12-d538-46b4-8001-cd46248a1f9f · outbound
This paper cites Muscriptor: An open model for multi-instrument music transcription, 2026.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Muscriptor: An open model for multi-instrument music transcription, 2026
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.673242Z
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.
Observation c226ce58-bccb-4284-878e-3145fae4044d · outbound
This paper cites Rick Rubin: The 60 minutes interview.60 Minutes, CBS News.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Rick Rubin: The 60 minutes interview.60 Minutes, CBS News
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.655671Z
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.
Observation 2c5f8fec-afaa-4ae4-a232-96c8a90cf810 · outbound
This paper cites an unresolved cited work.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Unresolved cited work
Reference 36
- Resolution
- unresolved
- raw_fallback, observed 2026-08-08T18:42:37.640139Z
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.
Observation 36cb00f1-254e-4088-8729-14943ecbb7c7 · outbound
This paper cites Improving and generalizing flow-based genera- tive models with minibatch optimal transport.Transactions on Machine Learning Research,.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Improving and generalizing flow-based genera- tive models with minibatch optimal transport.Transactions on Machine Learning Research,
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:42:37.093962Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ab69694a-1cbf-45f4-b5c5-310b296da0c0 · outbound
This paper cites Music-JEPA: Learning a world model of sound from action, 2026.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Music-JEPA: Learning a world model of sound from action, 2026
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.601766Z
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.
Observation ef97b942-4dd2-4979-ba95-68a7039b397d · outbound
This paper cites Visreg: Variance-invariance-sketching regularization for jepa training, 2026.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Visreg: Variance-invariance-sketching regularization for jepa training, 2026
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T18:42:37.585245Z
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.
Observation d4332ef1-0b75-4283-a70f-c45e98a78200 · outbound
This paper cites MelodyGLM: Multi-task Pre-training for Symbolic Melody Generation.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation MelodyGLM: Multi-task Pre-training for Symbolic Melody Generation
Reference 40
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T18:42:37.410262Z
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.
Observation 8564d54c-c355-4bf7-ade4-163d2526236d · outbound
This paper cites MIDI-LLaMA: An instruction-following multimodal LLM for symbolic music understanding.arXiv preprint arXiv:2601.21740, 2026.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation MIDI-LLaMA: An instruction-following multimodal LLM for symbolic music understanding.arXiv preprint arXiv:2601.21740, 2026
Reference 41
- Resolution
- verified exact
- raw_fallback, observed 2026-08-08T18:42:37.387019Z
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.
Observation b90d367e-3164-4d36-a123-753077ee38f0 · outbound
This paper cites ARIMA: Reconstruction-Grounded Predictive Representation Learning for Symbolic Music.
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
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T18:42:37.310363Z
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.
Observation d31e8fa0-d1c7-49c7-bad9-438cbb904560 · outbound
This paper cites ABC-Eval: Benchmarking large language models on symbolic music understanding and instruction following.arXiv preprint arXiv:2509.23350, 2025.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation ABC-Eval: Benchmarking large language models on symbolic music understanding and instruction following.arXiv preprint arXiv:2509.23350, 2025
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:42:37.128449Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9c36c57d-20fb-411d-b5cc-6c78bc1b0432 · outbound
This paper cites Diffusion Transformers with Representation Autoencoders.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Diffusion Transformers with Representation Autoencoders
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T18:42:37.133267Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c4c16f69-7feb-45d3-b797-efdfae11cf75 · outbound
This paper cites an unresolved cited work.
Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation Unresolved cited work
Reference 2024
- Resolution
- parse uncertain
- no resolver link, observed 2026-08-08T18:42:37.099100Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.