Paper Citation Record · LEDGER

Learning to Efficiently Sample from Diffusion Probabilistic Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2106.03802.

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

pith.paper-citation-record.v1
2106.03802 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 2026-08-09T06:31:02.800959+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:28:12.194823Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-11T01:57:49.885121Z

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 2ec2d784-06d1-4333-b18a-71e7dea62f3a · inbound

Progressive Distillation for Fast Sampling of Diffusion Models cites this paper.

Progressive Distillation for Fast Sampling of Diffusion Models Learning to Efficiently Sample from Diffusion Probabilistic Models

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T09:37:44.749148Z

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.

Observation f94db6c1-36df-4034-a7b4-958cf050cd17 · inbound

Elucidating the Design Space of Diffusion-Based Generative Models cites this paper.

Elucidating the Design Space of Diffusion-Based Generative Models Learning to Efficiently Sample from Diffusion Probabilistic Models

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-14T17:46:53.309256Z

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.

Observation 664e8fa2-cc32-4fdc-9e39-5aaaecd892b8 · inbound

Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference cites this paper.

Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference Learning to Efficiently Sample from Diffusion Probabilistic Models

Reference 88

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T04:15:54.852702Z

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.

Observation 694c90a5-d2a9-45af-81b2-942b202680a9 · inbound

2ndMatch: Finetuning Pruned Diffusion Models via Second-Order Jacobian Matching cites this paper.

2ndMatch: Finetuning Pruned Diffusion Models via Second-Order Jacobian Matching Learning to Efficiently Sample from Diffusion Probabilistic Models

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-05-19T12:12:16.966851Z

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.

Observation e1f55283-9aa7-4c1d-8032-e62b8ba90c1f · inbound

Morse: Dual-Sampling for Lossless Acceleration of Diffusion Models cites this paper.

Morse: Dual-Sampling for Lossless Acceleration of Diffusion Models Learning to Efficiently Sample from Diffusion Probabilistic Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T23:28:12.194823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecb5126d-e333-42ad-aef4-bc20beabf4e3 · inbound

Hierarchical Schedule Optimization for Fast and Robust Diffusion Model Sampling cites this paper.

Hierarchical Schedule Optimization for Fast and Robust Diffusion Model Sampling Learning to Efficiently Sample from Diffusion Probabilistic Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-21T20:00:33.913517Z

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.

Observation 23eae98a-1563-4e12-a5d9-5fe370545f15 · inbound

Sharpen Your Flow: Sharpness-Aware Sampling for Flow Matching cites this paper.

Sharpen Your Flow: Sharpness-Aware Sampling for Flow Matching Learning to Efficiently Sample from Diffusion Probabilistic Models

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T02:22:06.344023Z

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.

Observation c9f2130c-3235-429f-8b82-d6b7b0250740 · inbound

D2PO: Optimizing Diffusion Samplers via Dynamic Preference cites this paper.

D2PO: Optimizing Diffusion Samplers via Dynamic Preference Learning to Efficiently Sample from Diffusion Probabilistic Models

Reference 57

Resolution: metadata mismatch; local_arxiv, observed 2026-07-11T01:57:49.916384Z

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.