Paper Citation Record · LEDGER

Q-Diffusion: Quantizing Diffusion Models

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2302.04304.

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

pith.paper-citation-record.v1
2302.04304 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:36:01.422555Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T15:45:48.747982Z

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 49a99859-5dbb-47fd-94b4-2602fc404253 · inbound

Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models cites this paper.

Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models Q-Diffusion: Quantizing Diffusion Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T11:36:01.422555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c36eb70a-11f2-47ef-8c6e-aa137c79ec0c · inbound

CAT Pruning: Cluster-Aware Token Pruning For Text-to-Image Diffusion Models cites this paper.

CAT Pruning: Cluster-Aware Token Pruning For Text-to-Image Diffusion Models Q-Diffusion: Quantizing Diffusion Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T19:05:52.899605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d95f1001-e8a8-4adc-b50f-b96ef7d1a462 · inbound

Forecast then Calibrate: Feature Caching as ODE for Efficient Diffusion Transformers cites this paper.

Forecast then Calibrate: Feature Caching as ODE for Efficient Diffusion Transformers Q-Diffusion: Quantizing Diffusion Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T17:31:13.046427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c132c994-1042-473c-b8d5-7e6bccf64102 · 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 Q-Diffusion: Quantizing Diffusion Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-05T12:27:44.325182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0ad8cff-4b92-4077-8652-86a4fdee2655 · 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 Q-Diffusion: Quantizing Diffusion Models

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:21:07.986625Z

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.

Observation e5da01f5-61cd-4971-b213-717808db52a7 · inbound

OFA-Diffusion Compression: Compressing Diffusion Model in One-Shot Manner cites this paper.

OFA-Diffusion Compression: Compressing Diffusion Model in One-Shot Manner Q-Diffusion: Quantizing Diffusion Models

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:11:02.275990Z

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.

Observation b50a942c-e13d-44e0-b753-d53dfe48323f · inbound

AdaCluster: Adaptive Query-Key Clustering for Sparse Attention in Video Generation cites this paper.

AdaCluster: Adaptive Query-Key Clustering for Sparse Attention in Video Generation Q-Diffusion: Quantizing Diffusion Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:43:49.776552Z

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.

Observation 3ad43853-aab0-4cb3-b341-e64000ad351f · inbound

JuZhou 1.0 Technical Report: The First Edge-Native Text-to-Image Foundation Model Trained Entirely on China-Developed AI Accelerators cites this paper.

JuZhou 1.0 Technical Report: The First Edge-Native Text-to-Image Foundation Model Trained Entirely on China-Developed AI Accelerators Q-Diffusion: Quantizing Diffusion Models

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:45:48.749505Z

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.

Observation 3c085ed7-cc64-4866-a034-796922d3d03c · inbound

JuZhou 1.0 Technical Report: The First Edge-Native Text-to-Image Foundation Model Trained Entirely on China-Developed AI Accelerators cites this paper.

JuZhou 1.0 Technical Report: The First Edge-Native Text-to-Image Foundation Model Trained Entirely on China-Developed AI Accelerators Q-Diffusion: Quantizing Diffusion Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-12T11:46:50.520083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.