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Paper Citation Record · LEDGER

Post-training Quantization on Diffusion Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2211.15736.

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

pith.paper-citation-record.v1
2211.15736 v3

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:27:44.373448Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T05:25:56.632355Z

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 e19ebbc7-cb4e-4676-8e7a-7a42c7535d34 · inbound

Q-Sched: Pushing the Boundaries of Few-Step Diffusion Models with Quantization-Aware Scheduling cites this paper.

Q-Sched: Pushing the Boundaries of Few-Step Diffusion Models with Quantization-Aware Scheduling Post-training Quantization on Diffusion Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-05T12:27:44.373448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:27:44.373448Z digest=sha256:217299a32802545b152236f084d6b308f6bbecb0c0f506b9091330324a512573

Observation d78d1c73-0dfb-4b41-8da0-61280c727df3 · inbound

FP4 Explore, BF16 Train: Diffusion Reinforcement Learning via Efficient Rollout Scaling cites this paper.

FP4 Explore, BF16 Train: Diffusion Reinforcement Learning via Efficient Rollout Scaling Post-training Quantization on Diffusion Models

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:25:56.638266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T18:10:06.994557Z digest=sha256:142e64cd6c69155f300e92d1acc86b76eb17645afdee70c41954c9601af5141d