Paper Citation Record · LEDGER

Label-Efficient Semantic Segmentation with Diffusion Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2112.03126.

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

pith.paper-citation-record.v1
2112.03126 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:50:42.810013Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T08:44:14.108282Z

Reference resolution

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verified exact0
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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 026e5ea6-5c9f-4934-9f9e-cb3388fe8ed2 · inbound

DiFaReli++: Diffusion Face Relighting with Consistent Cast Shadows cites this paper.

DiFaReli++: Diffusion Face Relighting with Consistent Cast Shadows Label-Efficient Semantic Segmentation with Diffusion Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-24T08:44:14.111121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9f9d7254-22b5-491f-917b-8be87231eb18 · inbound

Medical Semantic Segmentation with Diffusion Pretrain cites this paper.

Medical Semantic Segmentation with Diffusion Pretrain Label-Efficient Semantic Segmentation with Diffusion Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T20:50:42.810013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e710feef-54de-40f5-b226-94cb27129ba1 · inbound

Exploring the latent space of diffusion models directly through singular value decomposition cites this paper.

Exploring the latent space of diffusion models directly through singular value decomposition Label-Efficient Semantic Segmentation with Diffusion Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T13:00:05.374361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 770be66a-b762-4493-8a3d-cb35658fbf49 · inbound

ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features cites this paper.

ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features Label-Efficient Semantic Segmentation with Diffusion Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-08T22:51:30.342260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04330d2f-57f1-4fe0-b2e8-b50412ef3e2a · inbound

Conditional diffusion model with spatial attention and latent embedding for medical image segmentation cites this paper.

Conditional diffusion model with spatial attention and latent embedding for medical image segmentation Label-Efficient Semantic Segmentation with Diffusion Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T14:11:54.432750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bc4db5b-28bb-4bfa-9ed3-46ec89f09d9a · inbound

gen2seg: Generative Models Enable Generalizable Instance Segmentation cites this paper.

gen2seg: Generative Models Enable Generalizable Instance Segmentation Label-Efficient Semantic Segmentation with Diffusion Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:31:40.568067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 72e20c05-4c01-4010-87e0-86d6874a4309 · inbound

SeaLion: Semantic Part-Aware Latent Point Diffusion Models for 3D Generation cites this paper.

SeaLion: Semantic Part-Aware Latent Point Diffusion Models for 3D Generation Label-Efficient Semantic Segmentation with Diffusion Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:45:42.795608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e8985c9-512c-428c-93aa-bc145611396f · inbound

CA-Diff: Collaborative Anatomy Diffusion for Brain Tissue Segmentation cites this paper.

CA-Diff: Collaborative Anatomy Diffusion for Brain Tissue Segmentation Label-Efficient Semantic Segmentation with Diffusion Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T22:01:15.286296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 438a0d5c-df02-4ee0-b4b2-9f7bf426e24e · inbound

Contrastive Learning with Diffusion Features for Weakly Supervised Medical Image Segmentation cites this paper.

Contrastive Learning with Diffusion Features for Weakly Supervised Medical Image Segmentation Label-Efficient Semantic Segmentation with Diffusion Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T21:46:33.750731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a33835f-19c3-4a6d-b1dc-6dfd2f29a28e · inbound

Heeding the Inner Voice: Aligning ControlNet Training via Intermediate Features Feedback cites this paper.

Heeding the Inner Voice: Aligning ControlNet Training via Intermediate Features Feedback Label-Efficient Semantic Segmentation with Diffusion Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T20:35:51.657841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e6e0f31-bae2-4047-959f-3614f7a7cbef · inbound

CPKD: Clinical Prior Knowledge-Constrained Diffusion Models for Surgical Phase Recognition in Endoscopic Submucosal Dissection cites this paper.

CPKD: Clinical Prior Knowledge-Constrained Diffusion Models for Surgical Phase Recognition in Endoscopic Submucosal Dissection Label-Efficient Semantic Segmentation with Diffusion Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T20:21:41.736235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37ac8200-9b03-43a2-b981-2f1251844155 · inbound

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model cites this paper.

Contrastive Conditional-Unconditional Alignment for Long-tailed Diffusion Model Label-Efficient Semantic Segmentation with Diffusion Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T18:12:43.141463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08e64d26-38da-44d1-afa9-a48060fe07fe · inbound

Latent Space Synergy: Text-Guided Data Augmentation for Direct Diffusion Biomedical Segmentation cites this paper.

Latent Space Synergy: Text-Guided Data Augmentation for Direct Diffusion Biomedical Segmentation Label-Efficient Semantic Segmentation with Diffusion Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T15:39:09.975730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 364298ec-df1d-45a5-a378-54f130c3a37e · inbound

Uni-DocDiff: A Unified Document Restoration Model Based on Diffusion cites this paper.

Uni-DocDiff: A Unified Document Restoration Model Based on Diffusion Label-Efficient Semantic Segmentation with Diffusion Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T01:00:39.124403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4098fa9-4e78-40d4-a090-828b87a090c3 · 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 Label-Efficient Semantic Segmentation with Diffusion Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T12:27:44.258086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b3fa7a2-b39b-4d4a-8ab2-95bce7826e08 · inbound

Revisiting Autoregressive Models for Generative Image Classification cites this paper.

Revisiting Autoregressive Models for Generative Image Classification Label-Efficient Semantic Segmentation with Diffusion Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-13T22:10:29.821610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9404a1fc-073c-455c-b4d2-34d5d8cff3de · inbound

SD-FSMIS: Adapting Stable Diffusion for Few-Shot Medical Image Segmentation cites this paper.

SD-FSMIS: Adapting Stable Diffusion for Few-Shot Medical Image Segmentation Label-Efficient Semantic Segmentation with Diffusion Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-13T21:08:18.368110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 125204e3-7f94-480a-b83c-f37f9ecadc58 · inbound

Diffusion Model as a Generalist Segmentation Learner cites this paper.

Diffusion Model as a Generalist Segmentation Learner Label-Efficient Semantic Segmentation with Diffusion Models

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T21:41:15.677242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 975a2509-2ca4-4861-a6b8-8b912f76ad7e · inbound

From Diffusion to Rectified Flow: Rethinking Text-Based Segmentation cites this paper.

From Diffusion to Rectified Flow: Rethinking Text-Based Segmentation Label-Efficient Semantic Segmentation with Diffusion Models

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:20:38.490714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 55e0eb00-3a7d-46f5-a60c-26ab71c77335 · inbound

JEDI: Joint Embedding Diffusion World Model for Online Model-Based Reinforcement Learning cites this paper.

JEDI: Joint Embedding Diffusion World Model for Online Model-Based Reinforcement Learning Label-Efficient Semantic Segmentation with Diffusion Models

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:37:51.881828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 90df406d-c705-469c-acb8-84f7ab75e6eb · inbound

Mutual Enhancement Between Global Tokens and Patch Tokens: From Theory to Practice cites this paper.

Mutual Enhancement Between Global Tokens and Patch Tokens: From Theory to Practice Label-Efficient Semantic Segmentation with Diffusion Models

Reference 78

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T22:43:50.954794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8ae0f3b9-d9ac-4f2f-8687-c1063dfa5d4b · inbound

Functionalization via Structure Completion and Motion Rectification cites this paper.

Functionalization via Structure Completion and Motion Rectification Label-Efficient Semantic Segmentation with Diffusion Models

Reference 168

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T12:28:16.968648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d28ad6f6-3364-43b2-a280-743f5ac85978 · inbound

What Makes Synthetic Data Effective in Image Segmentation cites this paper.

What Makes Synthetic Data Effective in Image Segmentation Label-Efficient Semantic Segmentation with Diffusion Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:13:06.697175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 95fd337a-0ef9-4158-8b8f-ac5186eed934 · inbound

Awakening Diffusion Transformers: Eliciting Stronger Generation and Understanding via Massive Activation Modulation cites this paper.

Awakening Diffusion Transformers: Eliciting Stronger Generation and Understanding via Massive Activation Modulation Label-Efficient Semantic Segmentation with Diffusion Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-12T05:46:45.293902Z

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Unavailable: canonical work link unavailable.

Observation ef3cd519-cc0f-407c-8d1f-42d6fca45f97 · inbound

Perturbation-Aware Diffusion-Guided Hybrid Segmentation for Robust and Annotation-Efficient Plant Stress Phenotyping cites this paper.

Perturbation-Aware Diffusion-Guided Hybrid Segmentation for Robust and Annotation-Efficient Plant Stress Phenotyping Label-Efficient Semantic Segmentation with Diffusion Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-30T16:08:47.774744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.