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Paper Citation Record · LEDGER

Scaling Diffusion Transformers to 16 Billion Parameters

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2407.11633.

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

pith.paper-citation-record.v1
2407.11633 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 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 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:48:08.836252Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:29:51.553624Z

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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 b23c2133-9d7d-4aa0-bb9c-172ebe497c3b · inbound

TripoSG: High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models cites this paper.

TripoSG: High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models Scaling Diffusion Transformers to 16 Billion Parameters

Reference 130

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arxiv_id, observed 2026-05-16T21:51:18.407630Z

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.

source=arxiv_source observed=2026-05-16T21:51:18.323840Z digest=sha256:c419f3e78823b45b815e74ff4d94655f7496baab55c8dd164929b25b1d38219d

Observation 0457c2e9-8435-4c79-a35c-a4b93868fea5 · inbound

InfLVG: Reinforce Inference-Time Consistent Long Video Generation with GRPO cites this paper.

InfLVG: Reinforce Inference-Time Consistent Long Video Generation with GRPO Scaling Diffusion Transformers to 16 Billion Parameters

Reference 13

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no resolver link, observed 2026-08-07T14:48:08.836252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation cf6e0aa0-502b-4c25-ba22-1a4fb7ee2bba · inbound

What Makes for Text to 360-degree Panorama Generation with Stable Diffusion? cites this paper.

What Makes for Text to 360-degree Panorama Generation with Stable Diffusion? Scaling Diffusion Transformers to 16 Billion Parameters

Reference 10

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no resolver link, observed 2026-08-07T13:19:37.074752Z

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Unavailable: canonical work link unavailable.

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Observation 2e6047fd-d2e7-4357-bb0d-e0918b761c85 · inbound

Exploring Diffusion Transformer Designs via Grafting cites this paper.

Exploring Diffusion Transformer Designs via Grafting Scaling Diffusion Transformers to 16 Billion Parameters

Reference 44

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no resolver link, observed 2026-08-07T10:29:04.328758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:29:04.328758Z digest=sha256:b0efac846e456a3a271aeb0bcea731a723249827a41be5c21e38cece5f380255

Observation 803a9246-8dc1-4443-b966-bb1a68ed1dd6 · inbound

InstructMoLE: Instruction-Guided Mixture of Low-rank Experts for Multi-Conditional Image Generation cites this paper.

InstructMoLE: Instruction-Guided Mixture of Low-rank Experts for Multi-Conditional Image Generation Scaling Diffusion Transformers to 16 Billion Parameters

Reference 8

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verified exact
arxiv_id, observed 2026-05-16T19:11:11.481573Z

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.

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Observation 13d40263-7642-4b4a-9034-658017713c9f · inbound

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models cites this paper.

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models Scaling Diffusion Transformers to 16 Billion Parameters

Reference 6

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no resolver link, observed 2026-08-03T05:23:12.364687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9ddf4b7e-0822-42e1-ab0e-c6cfabb00b76 · inbound

Large Spikes in Stochastic Gradient Descent: A Large-Deviations View cites this paper.

Large Spikes in Stochastic Gradient Descent: A Large-Deviations View Scaling Diffusion Transformers to 16 Billion Parameters

Reference 19

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verified exact
arxiv_id, observed 2026-05-15T13:30:51.065187Z

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.

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Observation 9edfe91d-2aa2-4c96-9a08-784104a11e98 · inbound

VersaVogue: Visual Expert Orchestration and Preference Alignment for Unified Fashion Synthesis cites this paper.

VersaVogue: Visual Expert Orchestration and Preference Alignment for Unified Fashion Synthesis Scaling Diffusion Transformers to 16 Billion Parameters

Reference 10

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verified exact
arxiv_id, observed 2026-05-10T23:35:51.227881Z

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.

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Observation 46399e47-ce42-4ad4-b29a-2ec33825b722 · inbound

CoInteract: Physically-Consistent Human-Object Interaction Video Synthesis via Spatially-Structured Co-Generation cites this paper.

CoInteract: Physically-Consistent Human-Object Interaction Video Synthesis via Spatially-Structured Co-Generation Scaling Diffusion Transformers to 16 Billion Parameters

Reference 8

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arxiv_id, observed 2026-05-11T12:41:04.295074Z

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.

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Observation 9dfbcbc5-4983-4af4-ba55-e7fdbc467e6a · inbound

Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE cites this paper.

Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE Scaling Diffusion Transformers to 16 Billion Parameters

Reference 12

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verified exact
arxiv_id, observed 2026-05-09T06:25:47.755152Z

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.

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Observation 46243908-2a23-4f57-af49-00684e85a5bb · inbound

From Articulated Kinematics to Routed Visual Control for Action-Conditioned Surgical Video Generation cites this paper.

From Articulated Kinematics to Routed Visual Control for Action-Conditioned Surgical Video Generation Scaling Diffusion Transformers to 16 Billion Parameters

Reference 17

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arxiv_id, observed 2026-05-12T03:16:18.741884Z

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.

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Observation 640c7b91-f43e-4319-80a2-be6aa4fa9b1f · inbound

Sparse Mixture-of-Experts Routing in Visual Diffusion Transformers:Diagnosis, Boundary Calibration and Evolutionary Roadmap from Routing Collapse to Selective Deadlock cites this paper.

Sparse Mixture-of-Experts Routing in Visual Diffusion Transformers:Diagnosis, Boundary Calibration and Evolutionary Roadmap from Routing Collapse to Selective Deadlock Scaling Diffusion Transformers to 16 Billion Parameters

Reference 18

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verified exact
arxiv_id, observed 2026-05-20T22:19:07.744410Z

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.

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Observation bc7f1cc7-c437-4905-88ed-63b2b4f69b9f · inbound

GenEraser: Generalizable Video Object Removal via Balanced Text-Mask Guidance and Decoupled Locator-Preserver cites this paper.

GenEraser: Generalizable Video Object Removal via Balanced Text-Mask Guidance and Decoupled Locator-Preserver Scaling Diffusion Transformers to 16 Billion Parameters

Reference 4

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arxiv_id, observed 2026-06-29T08:13:15.785911Z

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.

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Observation 8ffd2888-736f-4fd3-b109-77c09e1e192f · inbound

FocusDiT: Masking Queries in Diffusion Transformers for Fine-grained Image Generation cites this paper.

FocusDiT: Masking Queries in Diffusion Transformers for Fine-grained Image Generation Scaling Diffusion Transformers to 16 Billion Parameters

Reference 18

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verified exact
arxiv_id, observed 2026-07-01T22:26:17.384696Z

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.

source=pdf_text observed=2026-06-28T15:25:40.039365Z digest=sha256:70434a6ea52872c163c1132a7360ffc0a276bd6207d486246e5e91433f88975b

Observation 8eb39041-1ed1-419a-a21e-daf0a76c302b · inbound

MoECodec: Image Compression for joint human and machine perception via Mixture-of-Experts cites this paper.

MoECodec: Image Compression for joint human and machine perception via Mixture-of-Experts Scaling Diffusion Transformers to 16 Billion Parameters

Reference 19

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arxiv_id, observed 2026-07-04T07:39:38.918366Z

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.

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Observation 09281248-1b55-4f43-8395-3dae64a510e4 · inbound

WiSP: A Working-Set View of Mixture-of-Experts Serving on Extremely Low-Resource Hardware cites this paper.

WiSP: A Working-Set View of Mixture-of-Experts Serving on Extremely Low-Resource Hardware Scaling Diffusion Transformers to 16 Billion Parameters

Reference 4

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verified exact
arxiv_id, observed 2026-07-04T07:49:39.554229Z

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.

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Observation 863a6165-491b-484e-b9b0-7d7243267487 · inbound

DiT-Reward: Generative Representations for Text-to-Image Reward Modeling cites this paper.

DiT-Reward: Generative Representations for Text-to-Image Reward Modeling Scaling Diffusion Transformers to 16 Billion Parameters

Reference 87

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arxiv_id, observed 2026-07-04T10:39:45.923888Z

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.

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Observation a0c6d09a-9bb9-410d-949b-385da699b328 · inbound

Focusing on What Matters: Saliency-Harnessing Accurate Routing for Diffusion MoE cites this paper.

Focusing on What Matters: Saliency-Harnessing Accurate Routing for Diffusion MoE Scaling Diffusion Transformers to 16 Billion Parameters

Reference 9

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arxiv_id, observed 2026-07-04T13:29:51.555031Z

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.

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Observation 577ddb23-f9a7-4909-85d0-826e66616ab0 · inbound

Amplifying Membership Signal Through Chained Regeneration cites this paper.

Amplifying Membership Signal Through Chained Regeneration Scaling Diffusion Transformers to 16 Billion Parameters

Reference 13

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verified exact
arxiv_id, observed 2026-07-01T09:45:39.295011Z

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.

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Observation 8f79fd1d-70aa-4605-b446-d55acb4b781d · inbound

X-Stage: An Overlooked Pipeline Stage for Communication-Computation Overlap in DiT Inference cites this paper.

X-Stage: An Overlooked Pipeline Stage for Communication-Computation Overlap in DiT Inference Scaling Diffusion Transformers to 16 Billion Parameters

Reference 13

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Source-reported events for the cited work

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