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Paper Citation Record · LEDGER

Gradient Guidance for Diffusion Models: An Optimization Perspective

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2404.14743.

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

pith.paper-citation-record.v1
2404.14743 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:55:14.703873Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:26:24.919909Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
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  • malformed identifier0
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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 93cfe7ca-3d47-453b-97f7-ccfd25d57703 · inbound

Nonlinear Assimilation via Score-based Sequential Langevin Sampling cites this paper.

Nonlinear Assimilation via Score-based Sequential Langevin Sampling Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-23T17:03:12.546742Z

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.

source=arxiv_source observed=2026-05-23T17:00:36.064749Z digest=sha256:efba3c00ff971b5ccdc641103f71d5123e43b2b21a12b18f74c7ba95055b6552

Observation 2feb56d4-84a0-4303-a379-ecef849385d2 · inbound

Flow Matching Guide and Code cites this paper.

Flow Matching Guide and Code Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:28:14.062945Z

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.

source=arxiv_source observed=2026-05-12T10:28:14.014706Z digest=sha256:e3bfa574389a5e50102b90d341666a55d0943ea20d2d5e3c20c194784870e138

Observation 116fd617-db5a-4984-a7d9-6de48041da5e · inbound

CoDe: Blockwise Control for Denoising Diffusion Models cites this paper.

CoDe: Blockwise Control for Denoising Diffusion Models Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-09T17:10:17.045926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T17:10:17.045926Z digest=sha256:592f965c1916df301d671562e51825057bf9fed28add841f1ce2f0f29ee16e01

Observation d07a524e-7ca7-4b88-af9b-401b38a86a46 · inbound

Refining Alignment Framework for Diffusion Models with Intermediate-Step Preference Ranking cites this paper.

Refining Alignment Framework for Diffusion Models with Intermediate-Step Preference Ranking Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-09T18:55:14.703873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:55:14.703873Z digest=sha256:7a603282ac4bf249665cc56ef14539668a128606be55b37a7599044e4538e0d6

Observation 8a322aca-912b-4aa7-8e2e-149266647976 · inbound

When are Diffusion Priors Helpful in Sparse Reconstruction? A Study with Sparse-view CT cites this paper.

When are Diffusion Priors Helpful in Sparse Reconstruction? A Study with Sparse-view CT Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-09T11:14:00.227486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:14:00.227486Z digest=sha256:a11af5f5d4c390bc8b81f00a7441829de5253ff0cb58965a4abb137fb22b861a

Observation 9969ee47-21ad-4481-b3f4-363e42d61e8b · inbound

A First-order Generative Bilevel Optimization Framework for Diffusion Models cites this paper.

A First-order Generative Bilevel Optimization Framework for Diffusion Models Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T23:43:37.807285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:43:37.807285Z digest=sha256:acfec6c2305006a91546077a132d2203f98b870f333cbc42803cc53b4a680640

Observation 21ad3f4a-8f13-4fb1-9598-168fdd07bd19 · inbound

MMaDA: Multimodal Large Diffusion Language Models cites this paper.

MMaDA: Multimodal Large Diffusion Language Models Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 80

Resolution
verified exact
arxiv_id, observed 2026-05-15T14:50:59.868901Z

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.

source=pdf_text observed=2026-05-15T14:50:59.661153Z digest=sha256:5308da5362977c4257fb7d7a6fa71378d5138fd71261aa5b0ce2879879698d1a

Observation 9f3a3545-7dcb-47eb-b18a-55120cd63b88 · inbound

Scaling Image and Video Generation via Test-Time Evolutionary Search cites this paper.

Scaling Image and Video Generation via Test-Time Evolutionary Search Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T14:49:42.701836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:49:42.701836Z digest=sha256:b43236c64907b47c07f4c42327d42986c643233728995992c576e149f878517e

Observation f7b710fe-50d9-4110-91c3-906c1a2711f5 · inbound

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation cites this paper.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T11:58:38.208407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:58:38.208407Z digest=sha256:4660de0100c0b90e505ce4260a8ee45fd7ee681a8e6a4116a34ed66e2191262b

Observation d24272f8-9c4a-4ed4-b193-3ac49db65569 · inbound

Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach cites this paper.

Solving Inverse Problems via Diffusion-Based Priors: An Approximation-Free Ensemble Sampling Approach Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 110

Resolution
unresolved
no resolver link, observed 2026-08-07T10:54:50.046204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:54:50.046204Z digest=sha256:4502c6efbea88d451bc3a0275f5f8863c99df38cc7eece31091b7bb21a8cba5a

Observation a97cb007-cd59-49c9-8682-85279d24b011 · inbound

Why Settle for Mid: A Probabilistic Viewpoint to Spatial Relationship Alignment in Text-to-image Models cites this paper.

Why Settle for Mid: A Probabilistic Viewpoint to Spatial Relationship Alignment in Text-to-image Models Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T21:48:52.464757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:48:52.464757Z digest=sha256:e5a0054de7555b4643821448116d09f9c9fe6d9773439f9090c439fb7327d8c3

Observation a5feea8d-7175-412c-8958-6aea03dbb2fa · inbound

Controllable 3D Molecular Generation for Structure-Based Drug Design Through Bayesian Flow Networks and Gradient Integration cites this paper.

Controllable 3D Molecular Generation for Structure-Based Drug Design Through Bayesian Flow Networks and Gradient Integration Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-05T14:25:28.120881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:25:28.120881Z digest=sha256:034426950f0f8bcb7feb8cf2558869cae973eb02d4215300474dc4f39cb44463

Observation f703322d-d52b-41d0-a2ee-4f2f6277696c · inbound

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

Demystifying Multimodal Biomolecular Co-design With Intrinsic Geodesic Coupling Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 95

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T01:26:24.921563Z

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.

source=arxiv_source observed=2026-06-28T11:58:18.626259Z digest=sha256:bd1f5ba77fe05372c8c17362ebb3b9beb5c6a7842bfdb7c650183f0559dffcd1

Observation 8f03720c-298e-4372-b1a4-20b858522778 · inbound

LC-GRPO: Bridging Train-Inference Gap for Flow-Based GRPO with Langevin Correction cites this paper.

LC-GRPO: Bridging Train-Inference Gap for Flow-Based GRPO with Langevin Correction Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-08T05:54:32.453132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:54:32.453132Z digest=sha256:f46647df052a8c4382a11645089671789e5c5930db30d2cc8de00c0a88b735ed