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Paper Citation Record · LEDGER

Diffusion Model for Data-Driven Black-Box Optimization

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2403.13219.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2403.13219 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:48:18.460557Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-02T23:17:29.675726Z

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 b950f94a-4309-4a71-a490-c5444c04a74c · inbound

Compositional amortized inference for large-scale hierarchical Bayesian models cites this paper.

Compositional amortized inference for large-scale hierarchical Bayesian models Diffusion Model for Data-Driven Black-Box Optimization

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-22T14:24:53.563552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-22T14:23:35.960476Z digest=sha256:dcff546aa3e26e7d22be6264d86d6e010a9e6759c82798334e14658abb82466e

Observation 9e9d06f5-ff22-40b2-895d-6ab96ba0ade2 · inbound

ReGuidance: A Simple Diffusion Wrapper for Boosting Sample Quality on Hard Inverse Problems cites this paper.

ReGuidance: A Simple Diffusion Wrapper for Boosting Sample Quality on Hard Inverse Problems Diffusion Model for Data-Driven Black-Box Optimization

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T04:18:59.619714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:18:59.619714Z digest=sha256:a4cc95d8a4053d7aa0079438316217bbbd1866ab8c53cc346b7097f1a884cd7f

Observation f66708d6-c30e-48f7-8d3d-1398b0498ef8 · inbound

Provable Maximum Entropy Manifold Exploration via Diffusion Models cites this paper.

Provable Maximum Entropy Manifold Exploration via Diffusion Models Diffusion Model for Data-Driven Black-Box Optimization

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-15T19:48:18.460557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:48:18.460557Z digest=sha256:3f2ec724958988c502b42e7041924390e2c95909b2007a478287507c50ea87ee

Observation 35b38b14-be2d-4d3d-87cf-4609fde99f53 · inbound

Adjoint-Based Aerodynamic Shape Optimization with a Manifold Constraint Learned by Diffusion Models cites this paper.

Adjoint-Based Aerodynamic Shape Optimization with a Manifold Constraint Learned by Diffusion Models Diffusion Model for Data-Driven Black-Box Optimization

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T10:52:03.571266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:52:03.571266Z digest=sha256:96841dead3c386702dfc7ada1332efcf755095ebb4a0fea9a4b269e32f128307

Observation 9ab22c64-03f7-487c-adcf-9553fb48c5ce · inbound

A Reward-Directed Diffusion Framework for Generative Design Optimization cites this paper.

A Reward-Directed Diffusion Framework for Generative Design Optimization Diffusion Model for Data-Driven Black-Box Optimization

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T05:39:22.853514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:39:22.853514Z digest=sha256:6743cd976655393422c9b3a592bee3e442892060b27d4a27bd0f55502ff35096

Observation 65583cb6-020d-4182-9c02-356a5e2912c3 · inbound

On the Robustness of Distribution Support under Diffusion Guidance cites this paper.

On the Robustness of Distribution Support under Diffusion Guidance Diffusion Model for Data-Driven Black-Box Optimization

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:30:57.509957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-11T02:27:44.244764Z digest=sha256:b5871bf4165aff52d3e9c7a324e217eb8bced4a1acced8368305b46f9caf7fdb

Observation 268cfb32-0475-4f38-9a25-8e11d2ab43b2 · inbound

On the Robustness of Distribution Support under Diffusion Guidance cites this paper.

On the Robustness of Distribution Support under Diffusion Guidance Diffusion Model for Data-Driven Black-Box Optimization

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-05-25T06:35:24.762212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-25T06:34:46.801241Z digest=sha256:2fc9dc45d4a368650899a51408cad78cbe2c05501fbb6bed0f92d6f0380d5393

Observation 46e12a09-3fac-497a-a07c-56c7cfd0be84 · inbound

Regret Analysis of Guided Diffusion for Black-Box Optimization over Structured Inputs cites this paper.

Regret Analysis of Guided Diffusion for Black-Box Optimization over Structured Inputs Diffusion Model for Data-Driven Black-Box Optimization

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:11:23.305375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-12T03:40:48.470892Z digest=sha256:ed4e2d6b12720750e80d0d3ca51a83c84844d9cbd936330bc824eb7d0a6ff89a

Observation 37eb5f4b-89eb-402b-b063-4b2c28f7727b · inbound

Proximal-Based Generative Modeling for Bayesian Inverse Problems cites this paper.

Proximal-Based Generative Modeling for Bayesian Inverse Problems Diffusion Model for Data-Driven Black-Box Optimization

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-14T17:57:33.419806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-14T17:53:42.816596Z digest=sha256:fa4875e7a827b0dd22a41789a04943993289690d4cfbb47c003fc4173cc8cd78

Observation 78af476b-749b-48ec-8267-c75ae95079e8 · inbound

GOAL: Graph-based Objective-Aligned Diffusion Solvers for Dynamic Multi-Objective Optimization cites this paper.

GOAL: Graph-based Objective-Aligned Diffusion Solvers for Dynamic Multi-Objective Optimization Diffusion Model for Data-Driven Black-Box Optimization

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-20T07:18:07.102183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T07:14:39.757279Z digest=sha256:a28f7727293d7c8fa74f65a338e0186e82d6fad637d0606fadc03e3d1d1bfb9e

Observation 9caf8eab-6ea9-4fbc-8580-7a108cbe6c66 · inbound

Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised Learning cites this paper.

Multi-Objective Learning for Diffusion Models: A Statistical Theory under Semi-Supervised Learning Diffusion Model for Data-Driven Black-Box Optimization

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-06-30T12:34:39.417744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-30T12:09:27.409746Z digest=sha256:9f7ce81d3a564d680bd32d27593b801a06385d9d0660e8e681dcdb6d8e429e53

Observation cb3e9ed5-c877-49d4-928c-afb254c493f9 · inbound

Demystifying Multimodal Biomolecular Co-design With Intrinsic Geodesic Coupling cites this paper.

Demystifying Multimodal Biomolecular Co-design With Intrinsic Geodesic Coupling Diffusion Model for Data-Driven Black-Box Optimization

Reference 96

Resolution
verified exact
arxiv_id, observed 2026-07-02T01:26:24.918684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-06-28T11:58:18.626259Z digest=sha256:0236dfc224fc007b5f0b90d6b6994b24e5540ab1bce1373aeace12697f8799e3

Observation 4f9c4b2a-dfb8-4474-aa37-8939333e2965 · inbound

Improving Bayesian Optimization via Training-Aware Conditional Diffusion Models cites this paper.

Improving Bayesian Optimization via Training-Aware Conditional Diffusion Models Diffusion Model for Data-Driven Black-Box Optimization

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-07-02T23:17:29.677226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-27T18:19:41.476212Z digest=sha256:f3d05acc650f84cdc2d19b4f3e9bdb4e1786bed355ba3f7628123e139aeebfe3

Observation 00738d9f-d53c-4794-8a59-8a71df4df13f · inbound

Provable diffusion-based posterior sampling for linear inverse problems via DDIM cites this paper.

Provable diffusion-based posterior sampling for linear inverse problems via DDIM Diffusion Model for Data-Driven Black-Box Optimization

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-01T12:52:55.885061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T12:52:55.885061Z digest=sha256:ead3f2606f190fa8a78732e7ca67ca2bebeb3165554ca76c8ba57168071a562f

Observation 89ac9d85-0056-41ae-8ab1-25ce3f540c38 · inbound

Optimal Reward Shaping: Autonomous Car Parking Case Study cites this paper.

Optimal Reward Shaping: Autonomous Car Parking Case Study Diffusion Model for Data-Driven Black-Box Optimization

Reference 31

Resolution
unresolved
no resolver link, observed 2026-07-30T17:40:27.384689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T17:40:27.384689Z digest=sha256:ba410248651ad0f24759d82bba70eb0e1ddee6aab7c146bd8e645fab2b72bb8a