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Paper Citation Record · LEDGER

Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2404.13686.

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

pith.paper-citation-record.v1
2404.13686 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:09:43.381547Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T23:45:07.681571Z

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Outbound references

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Pith citing papers

Observation eb1fbafb-9e46-4a6e-bc90-9b0d5c6414cd · 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 Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 35

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no resolver link, observed 2026-08-12T21:18:03.858903Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T21:18:03.858903Z digest=sha256:b2e9f6d2764d342c5b628282dbb1ffd12ec359289e70a7bc4c18455de51d22c6

Observation 92f739c6-6661-4c0e-961d-f9360164b5f1 · inbound

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

Adversarial Diffusion Compression for Real-World Image Super-Resolution Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 72

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no resolver link, observed 2026-08-12T16:32:25.300258Z

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source=pdf_text observed=2026-08-12T16:32:25.300258Z digest=sha256:1ea8fdf182241c5aac9a2dd07695311a64724e3df735c593e0b3a399e0da16f2

Observation 152fcc5b-ca25-4faa-9f66-7947f650bb1f · inbound

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

NitroFusion: High-Fidelity Single-Step Diffusion through Dynamic Adversarial Training Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 37

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no resolver link, observed 2026-08-11T23:58:13.340657Z

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source=pdf_text observed=2026-08-11T23:58:13.340657Z digest=sha256:addfa643590b74a378f82d04fd2845e68bccb229295425dffb71390501dcdd34

Observation 662192fd-169e-42b0-b27f-5552616f6b5a · inbound

Panoptic Diffusion Models: co-generation of images and segmentation maps cites this paper.

Panoptic Diffusion Models: co-generation of images and segmentation maps Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 38

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no resolver link, observed 2026-08-11T23:02:16.415341Z

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source=arxiv_source observed=2026-08-11T23:02:16.415341Z digest=sha256:9d6a6351d613925ffa23984dea8fc6c6ce1bfc830a6afce356d7d751bd374635

Observation 39c5bb1f-b102-4169-beae-31c7b71ce684 · inbound

See Further When Clear: Curriculum Consistency Model cites this paper.

See Further When Clear: Curriculum Consistency Model Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 2021

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no resolver link, observed 2026-08-11T19:52:12.311791Z

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source=pdf_text observed=2026-08-11T19:52:12.311791Z digest=sha256:b5c3ba61db8e36c1f73472f4756be2a36522a727439be049718d021dc0bed72d

Observation 7459c5ba-db22-4f98-8377-6d615fd5693d · inbound

Single Trajectory Distillation for Accelerating Image and Video Style Transfer cites this paper.

Single Trajectory Distillation for Accelerating Image and Video Style Transfer Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 25

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source=pdf_text observed=2026-08-11T04:23:04.290662Z digest=sha256:54ac8dedfcf0f2903e2716503ea7dba0070aa69e7e1776cf37c2950d2991b4a8

Observation b414525b-8957-471b-8f6d-5fc575c640c7 · inbound

Improved Training Technique for Latent Consistency Models cites this paper.

Improved Training Technique for Latent Consistency Models Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 19

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no resolver link, observed 2026-08-09T15:20:57.635217Z

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source=pdf_text observed=2026-08-09T15:20:57.635217Z digest=sha256:ab6ccb14decd5cff417aaa4983fe2c2aec07ef858f650443ff0b405ec72fd6ca

Observation b15d7f19-78dc-4a73-b46e-59ace3e2603c · 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 Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 43

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source=pdf_text observed=2026-08-08T19:32:31.950210Z digest=sha256:8ef36b048863e55a164c7b768f54bc9908fcb47f9349622470a0ca69b218b92a

Observation 137da532-4418-4905-8731-6bb578cac9a0 · inbound

Fast Text-to-Audio Generation with Adversarial Post-Training cites this paper.

Fast Text-to-Audio Generation with Adversarial Post-Training Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 12

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source=pdf_text observed=2026-08-15T22:09:43.381547Z digest=sha256:af34028dd65ec8db38ce938d3c0c6c22d33d6ff0167048b85e56f5d1cbafde4d

Observation 8a0c538c-90f1-4594-9eeb-efd478f3d3f2 · inbound

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios cites this paper.

Aquarius: A Family of Industry-Level Video Generation Models for Marketing Scenarios Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 18

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source=pdf_text observed=2026-08-15T21:35:46.756193Z digest=sha256:0e453d132551bf277e7e67e090834bf0b0c9310ed1ebc741b1d8005a64e4ad04

Observation 07954744-a651-4b21-9045-977109fa8331 · inbound

FastFace: Tuning Identity Preservation in Distilled Diffusion via Guidance and Attention cites this paper.

FastFace: Tuning Identity Preservation in Distilled Diffusion via Guidance and Attention Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 10

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:44:25.259375Z digest=sha256:2123ba949c80a9115c6eee6d91f94baf79012a4c0f99941e38d68323c6d26e7a

Observation c4be0445-407e-470a-bb2f-4a0f061d8b54 · inbound

Dual-Expert Consistency Model for Efficient and High-Quality Video Generation cites this paper.

Dual-Expert Consistency Model for Efficient and High-Quality Video Generation Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 47

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source=pdf_text observed=2026-08-07T11:14:08.447768Z digest=sha256:60804c11ef761fc75453c5876c85a0510d24c696e62b34e2c494eb96c334a663

Observation 5d942bf0-6447-4b2c-b3af-a436f06b1ef3 · inbound

The Hidden Cost of an Image: Quantifying the Energy Consumption of AI Image Generation cites this paper.

The Hidden Cost of an Image: Quantifying the Energy Consumption of AI Image Generation Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 28

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source=pdf_text observed=2026-08-15T19:17:12.981381Z digest=sha256:3d26a12f68fa2e41e4ea0d0385e16982f36708c6058d171b14df410e5502bffc

Observation 43271464-f816-413c-8fa3-08e3100a3f34 · inbound

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning cites this paper.

ShortFT: Diffusion Model Alignment via Shortcut-based Fine-Tuning Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 37

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source=pdf_text observed=2026-08-06T11:32:42.637511Z digest=sha256:52671cfb6fe5552337303ff41560a3dcc10180db19ff5cc3ca3977aabf3304e8

Observation a3f57fec-6af9-4afb-bf20-e96af035ff87 · inbound

PixNerd: Pixel Neural Field Diffusion cites this paper.

PixNerd: Pixel Neural Field Diffusion Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 72

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source=pdf_text observed=2026-08-06T10:59:53.977618Z digest=sha256:09d7f471aa34b094c89ea0c02e0e46ea92ac9c0e7192c01e790bc6cdcb9b24db

Observation 9f03cb80-96d8-4bd4-b8ac-d288b2d50aa8 · inbound

Distribution Matching Distillation Meets Reinforcement Learning cites this paper.

Distribution Matching Distillation Meets Reinforcement Learning Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 40

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no resolver link, observed 2026-08-03T21:47:20.022789Z

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source=pdf_text observed=2026-08-03T21:47:20.022789Z digest=sha256:3be319ceb9cc69d6fd454be9aa0652563c896de4bc212d1ac07fc4c9d62a3258

Observation e214a253-e061-440d-8477-cbcb9c51816f · inbound

Salt: Self-Consistent Distribution Matching with Cache-Aware Training for Fast Video Generation cites this paper.

Salt: Self-Consistent Distribution Matching with Cache-Aware Training for Fast Video Generation Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 31

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arxiv_id, observed 2026-05-13T19:43:11.401727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-13T19:38:54.942114Z digest=sha256:83c6f1f0e0acad1dff6ec60a854982c3ea2ce8598822709573a7e7183cf26fe9

Observation 46096a7d-6a6a-4172-97fb-51a81d08372d · inbound

1.x-Distill: Breaking the Diversity, Quality, and Efficiency Barrier in Distribution Matching Distillation cites this paper.

1.x-Distill: Breaking the Diversity, Quality, and Efficiency Barrier in Distribution Matching Distillation Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 33

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arxiv_id, observed 2026-05-13T17:23:02.598887Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-13T17:19:49.891090Z digest=sha256:2889ca04ee9485273e6b75a458159dddd41e23d9cf4f66aa6b59b1842be96f1a

Observation d763d51d-84a9-480f-8034-c21d3e5f2db8 · inbound

Reward-Aware Trajectory Shaping for Few-step Visual Generation cites this paper.

Reward-Aware Trajectory Shaping for Few-step Visual Generation Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 27

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arxiv_id, observed 2026-05-10T11:45:21.309548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T11:43:55.499474Z digest=sha256:c0c65a954ceb67cbfb7c8c3f71b22816758a88adb464968c4671b279b2dbe98a

Observation ff32cacc-e0bf-475e-9bce-97b60c88455e · inbound

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models cites this paper.

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 75

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arxiv_id, observed 2026-05-11T17:36:05.789344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T17:25:26.391582Z digest=sha256:47f6dfc49a900c1aa421066683c975c44cee652993e80de2db2d4f6aac81201b

Observation 9948742a-8dad-4eac-93ce-7ba6b81d9726 · inbound

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models cites this paper.

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 76

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arxiv_id, observed 2026-05-20T23:19:13.619125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T23:18:35.390642Z digest=sha256:5857209964c585c55e050f6f577165934c24da3786e3fcddc012174aef8280bd

Observation 2f431a5c-ec05-4495-a53c-62f02462cc91 · inbound

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models cites this paper.

D-OPSD: On-Policy Self-Distillation for Continuously Tuning Step-Distilled Diffusion Models Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 76

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arxiv_id, observed 2026-06-30T23:45:07.683049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T23:44:10.302520Z digest=sha256:baf190c3a3193e71cec8ab9697fecf9cdce954de652269cf6a8d858e1d86f35c

Observation 16ed55b1-3fe3-4fc8-b19f-ef312cc43da4 · inbound

Systematic Optimization of Real-Time Diffusion Model Inference on Apple M3 Ultra cites this paper.

Systematic Optimization of Real-Time Diffusion Model Inference on Apple M3 Ultra Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 7

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arxiv_id, observed 2026-05-21T13:00:09.744939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-21T12:59:13.952052Z digest=sha256:40f9f23ec3785cb7c90472a592e34684d5d58c475da7a8331e26cd60575e4b02

Observation cb10a513-e47c-448b-b595-b8c58f21ee97 · inbound

A Decomposable Probe for Few-Step Diffusion Models: Prompt, Latent, and Score Selectivity across Backbone Families and Distillation Paradigms cites this paper.

A Decomposable Probe for Few-Step Diffusion Models: Prompt, Latent, and Score Selectivity across Backbone Families and Distillation Paradigms Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 82

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source=arxiv_source observed=2026-07-12T03:47:04.311886Z digest=sha256:a5765eaf76e8b1aa6b86333033e8fa795238f681835f749f935dce677a366f4a

Observation 18df3e63-b085-49dc-b6a2-60b408d9d962 · inbound

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing cites this paper.

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 67

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source=pdf_text observed=2026-08-01T13:39:00.878827Z digest=sha256:8fe52a02f5cfb01caccb81bef4519db5e128dad999f5927a0f88ec86de709f35

Observation 74ec435b-50b8-453a-b7f7-09522a8db38f · 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 Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis

Reference 56

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T15:15:58.128804Z digest=sha256:691173e7a7d4482beea60162305f70c0baf1f183c3c3292188dbe793620babdd