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Paper Citation Record · LEDGER

Diffusion-Sharpening: Fine-tuning Diffusion Models with Denoising Trajectory Sharpening

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.12146.

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

pith.paper-citation-record.v1
2502.12146 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:54:45.933964Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T14:50:59.855526Z

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 3df2197d-09f1-4cb0-9dbd-59dcb47bd885 · inbound

MMaDA: Multimodal Large Diffusion Language Models cites this paper.

MMaDA: Multimodal Large Diffusion Language Models Diffusion-Sharpening: Fine-tuning Diffusion Models with Denoising Trajectory Sharpening

Reference 78

Resolution
verified exact
arxiv_id, observed 2026-05-15T14:50:59.858515Z

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.

source=pdf_text observed=2026-05-15T14:50:59.661153Z digest=sha256:f68a46799ca601c059959daeedd025da4c807730d0625ddd3626c634d4c708ca

Observation 86a2a273-bc55-45ec-adcb-fa286c12a4df · inbound

Inversion-DPO: Precise and Efficient Post-Training for Diffusion Models cites this paper.

Inversion-DPO: Precise and Efficient Post-Training for Diffusion Models Diffusion-Sharpening: Fine-tuning Diffusion Models with Denoising Trajectory Sharpening

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T17:54:45.933964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:54:45.933964Z digest=sha256:3849f7eb86f5ce2c99c7d737a65bef06079d0eef8ec4b944605635d5846ccf21