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Paper Citation Record · LEDGER

Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2406.06382.

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

pith.paper-citation-record.v1
2406.06382 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:07:10.177735Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T23:42:16.524291Z

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 bceac320-9a14-4cae-aef3-b4acaae86723 · inbound

DyMO: Training-Free Diffusion Model Alignment with Dynamic Multi-Objective Scheduling cites this paper.

DyMO: Training-Free Diffusion Model Alignment with Dynamic Multi-Objective Scheduling Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-12T05:07:10.177735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:07:10.177735Z digest=sha256:03cb0f389edcc2bd085f12a17a5dae95b008d9c1af4b72a9b9cf5056e7a1ade6

Observation 03b32048-f7ac-474a-9738-c5fb36383d8c · inbound

CoMPaSS: Enhancing Spatial Understanding in Text-to-Image Diffusion Models cites this paper.

CoMPaSS: Enhancing Spatial Understanding in Text-to-Image Diffusion Models Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T13:24:10.602422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:24:10.602422Z digest=sha256:7b676789263d064de5a425e693e21b75e7430de473463c7f119169fbd1218cbc

Observation 1a050560-9af7-49f2-ac32-16f68a6c059c · inbound

BalancedDPO: Adaptive Multi-Metric Alignment cites this paper.

BalancedDPO: Adaptive Multi-Metric Alignment Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-22T23:42:16.528205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-22T23:37:55.154902Z digest=sha256:2af0e3900f379b60bc9f2fcc93a897cb1c0a9d3ab51411d097dfff6df913f22d

Observation 0f6310d3-adc3-4503-84eb-d22f889af12d · inbound

Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences cites this paper.

Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T11:26:56.581759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:26:56.581759Z digest=sha256:949a88c1ecc147ced44e1b8e565210cf36a599aefcc284b859a60b0a6ac2960a

Observation 95482ed2-8fe3-4f0a-a457-c4fc943a3e83 · inbound

Direct Diffusion Score Preference Optimization via Stepwise Contrastive Policy-Pair Supervision cites this paper.

Direct Diffusion Score Preference Optimization via Stepwise Contrastive Policy-Pair Supervision Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-03T13:45:02.749981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:45:02.749981Z digest=sha256:887ff638cb7806f96dce1452a12903dff49fc9c7fe9110313fccaa7013ec98fd

Observation cdc4a610-543c-4626-af15-7e56d7838dc1 · inbound

RL-RIG: A Generative Spatial Reasoner via Intrinsic Reflection cites this paper.

RL-RIG: A Generative Spatial Reasoner via Intrinsic Reflection Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-15T20:36:35.337700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-15T20:33:09.627731Z digest=sha256:563de74623c509932aa2c2dd2eda5d895eca3e99f6b689d877a30af1716f6999

Observation 01cbd7a1-b380-42eb-8960-7add3f0ea094 · inbound

Towards General Preference Alignment: Diffusion Models at Nash Equilibrium cites this paper.

Towards General Preference Alignment: Diffusion Models at Nash Equilibrium Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:56:07.008366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-08T16:54:58.732444Z digest=sha256:88bbd0e194f0806e5b1c5ee9844d33c45ec89914f9d91e4142d507ca81b6e0b2

Observation 13fe8cee-1e61-42bc-811a-126fcf34bdb7 · inbound

Power Reinforcement Post-Training of Text-to-Image Models with Super-Linear Advantage Shaping cites this paper.

Power Reinforcement Post-Training of Text-to-Image Models with Super-Linear Advantage Shaping Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:16:29.380527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-12T03:33:40.994346Z digest=sha256:1727b658567940ccc53dd6ed70af1cc22065c32a3a5f9871039ab81f94afc5b7