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Paper Citation Record · LEDGER

Multistep Consistency Models

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 28 inbound Pith citation observations for arXiv:2403.06807.

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

pith.paper-citation-record.v1
2403.06807 v3

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:15:58.138478Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:29:59.509159Z

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c6ae3345-98ec-458e-a196-af4fc297f522 · inbound

Inconsistencies In Consistency Models: Better ODE Solving Does Not Imply Better Samples cites this paper.

Inconsistencies In Consistency Models: Better ODE Solving Does Not Imply Better Samples Multistep Consistency Models

Reference 10

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source=pdf_text observed=2026-08-12T21:18:03.761570Z digest=sha256:8caf3bbe39e9d08011cecaba2da60b875f54fbcbf14284aea687a6f21b06fecf

Observation 7b480d1c-416b-4596-b269-9b363c0f84f5 · inbound

Adversarial Diffusion Compression for Real-World Image Super-Resolution cites this paper.

Adversarial Diffusion Compression for Real-World Image Super-Resolution Multistep Consistency Models

Reference 29

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source=pdf_text observed=2026-08-12T16:32:25.127309Z digest=sha256:7dae00c28b1364efa133860a65f1e78de6d4af8c5b36cbdd067763cf245e3452

Observation cdd14c90-05d3-493f-9b4f-dc23e20da948 · inbound

NitroFusion: High-Fidelity Single-Step Diffusion through Dynamic Adversarial Training cites this paper.

NitroFusion: High-Fidelity Single-Step Diffusion through Dynamic Adversarial Training Multistep Consistency Models

Reference 15

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source=pdf_text observed=2026-08-11T23:58:13.229826Z digest=sha256:18e22ab794552bf0890218f518fa07ecddb0424e1c023ec17a324aa77f5f8981

Observation d931c44c-73c9-4665-b0b7-63ddb5e74975 · inbound

Improved Training Technique for Latent Consistency Models cites this paper.

Improved Training Technique for Latent Consistency Models Multistep Consistency Models

Reference 6

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source=pdf_text observed=2026-08-09T15:20:57.572858Z digest=sha256:be49fc5c7fc691ab2436cd1f6b70e5021127283d7b9d992b6e2c4f93a9e1fb17

Observation 3970dfbc-d387-4fe7-ae33-5ac3a22f2475 · inbound

UniCMs: A Unified Consistency Model For Efficient Multimodal Generation and Understanding cites this paper.

UniCMs: A Unified Consistency Model For Efficient Multimodal Generation and Understanding Multistep Consistency Models

Reference 17

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source=pdf_text observed=2026-08-08T19:32:31.834011Z digest=sha256:be66815d7137b0f574140a079f0e1443757a59fb86d3dfa56f6339219a25b11a

Observation 81427793-320b-4014-a568-6d264499d586 · inbound

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile cites this paper.

Efficient-vDiT: Efficient Video Diffusion Transformers With Attention Tile Multistep Consistency Models

Reference 15

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source=arxiv_source observed=2026-08-08T16:36:00.613132Z digest=sha256:f9e1ed3cd7fa7c2658000bcd7dfac5e9a22a4564a538da347797f5be84e1f3e7

Observation 6421a752-fccf-4943-81cb-411a0184a9cc · inbound

Continuous Semi-Implicit Models cites this paper.

Continuous Semi-Implicit Models Multistep Consistency Models

Reference 13

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source=arxiv_source observed=2026-08-07T05:59:16.154693Z digest=sha256:1a15d2d62d602af4ec1bfc12acb8d7747a5966f9cd2e5f0c18eba0a49497e875

Observation 3797d1af-b317-4430-8c39-ac6e39dc48ce · inbound

SplitMeanFlow: Interval Splitting Consistency in Few-Step Generative Modeling cites this paper.

SplitMeanFlow: Interval Splitting Consistency in Few-Step Generative Modeling Multistep Consistency Models

Reference 11

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source=pdf_text observed=2026-08-06T15:07:27.260716Z digest=sha256:dd4156c0d2982419248a6dcfe845fddbb3d418b7c4de1f0aac8844d4483c6ac7

Observation 58474512-516e-414b-bcff-7907dc0816ed · inbound

A Continuous-Time Consistency Model for 3D Point Cloud Generation cites this paper.

A Continuous-Time Consistency Model for 3D Point Cloud Generation Multistep Consistency Models

Reference 12

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source=pdf_text observed=2026-08-05T12:43:32.291340Z digest=sha256:c2c154a06b9b1ee7e4ff5e198be6a9f7efb8ba789edab6f727f87628a081c0d7

Observation 277e6b13-bde6-4c47-abd4-4d5ff8d918a3 · inbound

MACS: Measurement-Aware Consistency Sampling for Inverse Problems cites this paper.

MACS: Measurement-Aware Consistency Sampling for Inverse Problems Multistep Consistency Models

Reference 42

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source=pdf_text observed=2026-08-04T12:45:32.918748Z digest=sha256:33d42a26a31f58b978b5d973a239edf65cb177337e1d11700caa8d26a8b8bf1e

Observation 0c44b7ed-a26a-4cde-ace7-757405815e00 · inbound

Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency cites this paper.

Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency Multistep Consistency Models

Reference 7

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arxiv_id, observed 2026-05-18T08:51:09.220373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T08:46:16.541104Z digest=sha256:11f3bbc185a8a2c20762f858d6b67a73b4f9524511d740a6655b17ca78a05221

Observation 5a781aac-a068-4682-80d1-420c3c343890 · inbound

Understanding, Accelerating, and Improving MeanFlow Training cites this paper.

Understanding, Accelerating, and Improving MeanFlow Training Multistep Consistency Models

Reference 26

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source=pdf_text observed=2026-08-03T20:39:16.113760Z digest=sha256:c45613aec7b999410342fa54430599b5fd81d70b7bfc289c9add072876e28861

Observation 3628b7ae-e787-449c-8001-1a94be04229d · inbound

Consistency Deep Equilibrium Models cites this paper.

Consistency Deep Equilibrium Models Multistep Consistency Models

Reference 2025

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source=pdf_text observed=2026-08-03T05:14:19.142425Z digest=sha256:f1656fbea727b4dcf9499e6af7863a77cc414c4121a22fd9d03961ebcc05f281

Observation a8c39c5c-7cb2-4103-9a04-80d108e45b6a · inbound

Heterogeneous Decentralized Diffusion Models cites this paper.

Heterogeneous Decentralized Diffusion Models Multistep Consistency Models

Reference 7

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source=pdf_text observed=2026-07-15T14:03:19.278198Z digest=sha256:b14fcc669469f485ad0a4d3115e27ad7ddb62460a40225e020a137484cf08ead

Observation fb47b92f-8ec9-44ec-bc58-dd877e736f30 · inbound

Heterogeneous Decentralized Diffusion Models cites this paper.

Heterogeneous Decentralized Diffusion Models Multistep Consistency Models

Reference 7

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source=pdf_text observed=2026-08-04T05:55:55.537035Z digest=sha256:5b7fd56757c84436e4e35e541c7ac795469f2fd32f37b253f5f0b54282f9787a

Observation 24eaa755-7c05-4d82-ba2f-06434762e7f7 · inbound

Extending One-Step Image Generation from Class Labels to Text via Discriminative Text Representation cites this paper.

Extending One-Step Image Generation from Class Labels to Text via Discriminative Text Representation Multistep Consistency Models

Reference 6

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arxiv_id, observed 2026-05-10T09:28:39.551210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T05:15:22.907880Z digest=sha256:088b5164885e5b0f05090e73e3ce63205c5ad1f89296f5a3f05e604c14cc515f

Observation 1dc0f8e3-3063-4fc9-9180-72dd688a13f1 · inbound

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond cites this paper.

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond Multistep Consistency Models

Reference 133

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arxiv_id, observed 2026-05-11T19:26:07.967855Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-08T12:02:07.027775Z digest=sha256:e57f0914e91b74633934d7da3d806f370583c30cad2f8b45301dc0229892c5dc

Observation 349f70b0-b0f8-4044-9f84-fea4b1153fc9 · inbound

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond cites this paper.

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond Multistep Consistency Models

Reference 133

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arxiv_id, observed 2026-07-04T17:29:59.526734Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-07-04T17:29:43.764085Z digest=sha256:c293eeff2286448026450a2e7ccfd76853222e50aeea7bbe8192cf311611c654

Observation 9304d44a-9d16-4c24-8377-78f11b8c4c9c · inbound

How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance cites this paper.

How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance Multistep Consistency Models

Reference 49

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arxiv_id, observed 2026-05-12T09:46:26.579503Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-07T09:24:42.020782Z digest=sha256:c54dc7bec962a41a858a5a4b935849d44c99439440efbe44f62f79bcdaf6c8f5

Observation d1ee4a03-9930-4e35-8c17-a018d0e6146a · inbound

How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance cites this paper.

How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance Multistep Consistency Models

Reference 49

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arxiv_id, observed 2026-05-21T09:29:57.107664Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-21T09:25:19.439423Z digest=sha256:84554b1036adf4ee5ba9c07117cd9327df807436043b475ae6a84224b64b15c2

Observation 74fa4091-e9ff-463f-b6cc-b0a857f54adf · inbound

How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance cites this paper.

How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance Multistep Consistency Models

Reference 49

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arxiv_id, observed 2026-07-01T08:25:33.256889Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-07-01T08:19:37.044714Z digest=sha256:c6c111433da80dfc0c792343a07e28d9e0eb458b9c7483a7452573a983c195f3

Observation e7f7e573-66b9-4465-a914-adf3aa7acb27 · inbound

Consistent Diffusion Language Models cites this paper.

Consistent Diffusion Language Models Multistep Consistency Models

Reference 53

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arxiv_id, observed 2026-05-11T14:51:04.778737Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-09T20:59:46.082251Z digest=sha256:41c1ed891d22e0f6937947bd98c2591ea33076826bf5dfc29d1b39aa8d7536f8

Observation 6bc29e70-434e-4a79-9f6d-239cb88bc6b2 · inbound

Trajectory-Consistent Flow Matching for Robust Visuomotor Policy Learning cites this paper.

Trajectory-Consistent Flow Matching for Robust Visuomotor Policy Learning Multistep Consistency Models

Reference 19

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arxiv_id, observed 2026-05-12T07:46:26.816916Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-12T01:57:45.978990Z digest=sha256:39ccec1007424f04c7cb098096a415de2f5de1a508c892925579df606d6b1db8

Observation 81d3761d-c354-4777-865c-c6c31e37cbf2 · inbound

Covariance-aware sampling for Diffusion Models cites this paper.

Covariance-aware sampling for Diffusion Models Multistep Consistency Models

Reference 7

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arxiv_id, observed 2026-05-15T03:08:57.702618Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-15T03:07:55.756947Z digest=sha256:021ccb4ea008882f3c0df212e6e4250741f222656dc0bf7666650ff26fed1883

Observation 853f75f7-3531-43cc-a1a1-e07375fa0aeb · inbound

Diffusion Fine-tuning with Rewarded Moment Matching Distillation cites this paper.

Diffusion Fine-tuning with Rewarded Moment Matching Distillation Multistep Consistency Models

Reference 5

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arxiv_id, observed 2026-06-30T07:14:21.815342Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-30T06:56:00.246628Z digest=sha256:6a4eda4ff3c0ba42ae920ec7b25a293f8893e2fa9f33d4a41ecd99002dbe42e0

Observation 90c74826-2617-45b7-a4eb-a50f8b8c3915 · inbound

Amortized Moment Matching for Visual Generation cites this paper.

Amortized Moment Matching for Visual Generation Multistep Consistency Models

Reference 11

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source=arxiv_source observed=2026-07-30T18:58:27.814868Z digest=sha256:21a474c12f584cbf4a5082619fa8e53eefe331bf6b50022b043bf83c4a3b349b

Observation 1b60c18a-1793-4e9b-949a-0ec65e25111e · inbound

TurboClear: One-Step Object-Effect Removal via Region-Calibrated Distribution Matching and Fusion cites this paper.

TurboClear: One-Step Object-Effect Removal via Region-Calibrated Distribution Matching and Fusion Multistep Consistency Models

Reference 58

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source=arxiv_source observed=2026-08-15T15:15:58.138478Z digest=sha256:aa40d0273fe85ee54034fc3554099022649eddbc930e620c0bc3c1e4df0b4d86

Observation 1f2d209b-9e24-447b-8bad-28bbd507b258 · inbound

DUET: A Diversity-Quality Duet of Distillation Experts for Two-Step Video Generation cites this paper.

DUET: A Diversity-Quality Duet of Distillation Experts for Two-Step Video Generation Multistep Consistency Models

Reference 37

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source=arxiv_source observed=2026-08-11T13:43:35.050380Z digest=sha256:2c02002a558d216ae3a906ab66236dd39c36e2ddb87eeb560026bd7bb1bf17b6