Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2404.15766.
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 2026-05-20T05:52:14.089334Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T05:53:04.604762Z
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 b2a7d0c3-fc8e-4e07-b8be-fb2ba7c02feb · inbound
Large Language Diffusion Models cites this paper.
Large Language Diffusion Models Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
Reference 56
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T01:42:54.476999Z
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 82d4db9d-1bb7-442d-a71c-07dc8d9c0f1e · inbound
LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning cites this paper.
LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
Reference 99
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T03:46:06.327035Z
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 81d30b00-5d40-4e4f-8950-8e3f85573427 · inbound
Incomplete Data, Complete Dynamics: A Diffusion Approach cites this paper.
Incomplete Data, Complete Dynamics: A Diffusion Approach Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T14:21:28.297603Z
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 2069a800-18f6-4083-93f6-90ea9ef687b5 · inbound
Discrete Bayesian Sample Inference for Graph Generation cites this paper.
Discrete Bayesian Sample Inference for Graph Generation Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T00:45:33.039614Z
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 1afee7ff-2ab3-4419-b1ce-154f7cf58aff · inbound
A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models cites this paper.
A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
Reference 51
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T04:35:59.419116Z
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 7f6e40b5-4247-4dfc-bbf5-a76c9f1b91a1 · inbound
Observation-Aligned Mask Priors for Learning Physical Dynamics from Authentic Occlusions cites this paper.
Observation-Aligned Mask Priors for Learning Physical Dynamics from Authentic Occlusions Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T21:02:47.291395Z
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 c1ceb7d8-81fb-418e-b237-110b0c5c9b93 · inbound
Efficient Long-Context Modeling in Diffusion Language Models via Block Approximate Sparse Attention cites this paper.
Efficient Long-Context Modeling in Diffusion Language Models via Block Approximate Sparse Attention Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T05:53:04.606868Z
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.