Paper Citation Record · LEDGER

Test-time Alignment of Diffusion Models without Reward Over-optimization

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2501.05803.

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

pith.paper-citation-record.v1
2501.05803 v3

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 2026-08-20T06:33:59.587034+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:34:44.534717Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:27:08.351367Z

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 22dec784-d49f-47ec-b02c-bd336abb8855 · inbound

Superbunched random fiber laser cites this paper.

Superbunched random fiber laser Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-13T20:31:07.902275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4833207b-25cf-4f6d-bb78-6821342c89ed · inbound

VASR: Variance-Aware Systematic Resampling for Reward-Guided Diffusion cites this paper.

VASR: Variance-Aware Systematic Resampling for Reward-Guided Diffusion Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:26:00.645366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c3104b73-bff4-4f89-96cb-623e02031052 · inbound

VASR: Variance-Aware Systematic Resampling for Reward-Guided Diffusion cites this paper.

VASR: Variance-Aware Systematic Resampling for Reward-Guided Diffusion Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:52:06.617032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5cd11bab-90ed-43c9-889f-61cfcaf05271 · inbound

Step-level Denoising-time Diffusion Alignment with Multiple Objectives cites this paper.

Step-level Denoising-time Diffusion Alignment with Multiple Objectives Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:15:25.858703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f779475f-4adb-40fd-b3e3-c79df87b0a01 · inbound

Dependency-Aware Discrete Diffusion for Scene Graph Generation cites this paper.

Dependency-Aware Discrete Diffusion for Scene Graph Generation Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:06:15.096632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 659cff2e-f249-4ff5-9109-cf4335076c5f · inbound

Do Less, Achieve More: Do We Need Every-Step Optimization for RL Fine-tuning of Diffusion Models? cites this paper.

Do Less, Achieve More: Do We Need Every-Step Optimization for RL Fine-tuning of Diffusion Models? Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:48:57.344161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b8a0d17c-f2a5-4d1b-9ac9-23df19db37c2 · inbound

Inference-Time Scaling in Diffusion Models through Iterative Partial Refinement cites this paper.

Inference-Time Scaling in Diffusion Models through Iterative Partial Refinement Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T06:53:05.982705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 50a8028e-7bfd-414d-8fdf-9a2a53d5df50 · inbound

Reflection Separation from a Single Image via Joint Latent Diffusion cites this paper.

Reflection Separation from a Single Image via Joint Latent Diffusion Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:36:27.332101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e08469f1-9303-4488-8fcd-27259df6430a · inbound

Generative Refinement for Low-Budget Black-Box Optimization cites this paper.

Generative Refinement for Low-Budget Black-Box Optimization Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:27:08.352835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation dd719fb7-ef0b-4e88-ac3d-79f024d6d80e · inbound

Sequentially-Controlled Interactive Multi-Particle Flow-Maps for Online Feedback-Driven Search cites this paper.

Sequentially-Controlled Interactive Multi-Particle Flow-Maps for Online Feedback-Driven Search Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-02T15:37:06.073893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a43922f5-fe81-43aa-ac45-82319f87d8a4 · inbound

Post-Generation Curation of Synthetic Images via Homogeneous-Heterogeneous Splitting cites this paper.

Post-Generation Curation of Synthetic Images via Homogeneous-Heterogeneous Splitting Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-12T08:12:18.373103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35575409-6510-4254-99fc-9ca94474649b · inbound

Bootstrap Flow-Map Tree Sampling Enables Online Feedback Driven Search cites this paper.

Bootstrap Flow-Map Tree Sampling Enables Online Feedback Driven Search Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-12T06:09:18.074799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b04c4f2a-5573-4d32-b798-631d479b788f · inbound

From Open Loop to Closed Loop: A Test-Time Iterative Optimization Framework for Reference-Consistent Image Generation cites this paper.

From Open Loop to Closed Loop: A Test-Time Iterative Optimization Framework for Reference-Consistent Image Generation Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-11T15:05:11.166049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a70ad3d7-53b2-4cba-8d3b-6f530b38f9a5 · inbound

PAST: Prompt-Adaptive Sampling Termination for Efficient Diffusion Model cites this paper.

PAST: Prompt-Adaptive Sampling Termination for Efficient Diffusion Model Test-time Alignment of Diffusion Models without Reward Over-optimization

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T14:34:44.534717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.