Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2409.09214.
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 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T23:43:03.212977Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T04:46:38.046767Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 6e25e813-d686-4e04-899a-d40a94449976 · inbound
Towards Hallucination-Free Music: A Reinforcement Learning Preference Optimization Framework for Reliable Song Generation cites this paper.
Towards Hallucination-Free Music: A Reinforcement Learning Preference Optimization Framework for Reliable Song Generation Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T23:43:03.212977Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f1525e8c-2d93-4968-92a5-4dc9c63c166e · inbound
LaDA-Band: Language Diffusion Models for Vocal-to-Accompaniment Generation cites this paper.
LaDA-Band: Language Diffusion Models for Vocal-to-Accompaniment Generation Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T09:16:01.555021Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a363e8fa-eccb-4ec0-8580-a5bf198229eb · inbound
LaDA-Band: Language Diffusion Models for Vocal-to-Accompaniment Generation cites this paper.
LaDA-Band: Language Diffusion Models for Vocal-to-Accompaniment Generation Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T16:27:21.042833Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f88f576d-7dca-4ae3-aa91-12d03df208e1 · inbound
Aligning Language Models for Lyric-to-Melody Generation with Rule-Based Musical Constraints cites this paper.
Aligning Language Models for Lyric-to-Melody Generation with Rule-Based Musical Constraints Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T12:41:05.132344Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation bafee1ff-3d6c-4aff-b2eb-ffd49878895b · inbound
Latent Space Disentanglement via Activation Steering for Interpretable Attribute Control in Symbolic Music Generation cites this paper.
Latent Space Disentanglement via Activation Steering for Interpretable Attribute Control in Symbolic Music Generation Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T20:26:12.945927Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f2f6ead4-267f-43f6-8238-4d31da06be5d · inbound
UniVocal: Unified Speech-Singing Code-Switching Synthesis cites this paper.
UniVocal: Unified Speech-Singing Code-Switching Synthesis Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Reference 50
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T00:46:24.579926Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ddceba15-82dc-4022-9073-154217ac5ad3 · inbound
JenBridge: Adaptive Long-Form Video Soundtracking across Scene Transitions cites this paper.
JenBridge: Adaptive Long-Form Video Soundtracking across Scene Transitions Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T00:56:24.636627Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0ed42ed1-e0fa-4177-8fe6-e8f24bcb8edc · inbound
SketchSong: Hierarchical Song Generation with Sketch Planning and Fine-Grained Multi-Track Modeling cites this paper.
SketchSong: Hierarchical Song Generation with Sketch Planning and Fine-Grained Multi-Track Modeling Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T04:46:38.049941Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation cfa0112b-63d2-405f-9aac-410d186266e4 · inbound
Stable Autoregressive Speech Generation with Low-Frame-Rate High-Dimensional Continuous Tokens cites this paper.
Stable Autoregressive Speech Generation with Low-Frame-Rate High-Dimensional Continuous Tokens Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T08:35:46.341782Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.