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Paper Citation Record · LEDGER

From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 24 inbound Pith citation observations for arXiv:2503.06923.

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

pith.paper-citation-record.v1
2503.06923 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:51:05.401910Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T12:15:01.137692Z

Reference resolution

0 of 0 outbound references displayed

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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 8f1e34e4-af45-4e1e-a329-a8bf8030d791 · inbound

PAROAttention: Pattern-Aware ReOrdering for Efficient Sparse and Quantized Attention in Visual Generation Models cites this paper.

PAROAttention: Pattern-Aware ReOrdering for Efficient Sparse and Quantized Attention in Visual Generation Models From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 30

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unresolved
no resolver link, observed 2026-08-06T23:51:05.401910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:51:05.401910Z digest=sha256:69983fe398fae382fdd30ed5e06f15ff30bd4a8acbbf31872afcbaf6f0f5f388

Observation 48daf06f-c958-47d3-8c6d-87e1c8cd83f6 · inbound

FlashEdit: Decoupling Speed, Structure, and Semantics for Precise Image Editing cites this paper.

FlashEdit: Decoupling Speed, Structure, and Semantics for Precise Image Editing From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 23

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verified exact
arxiv_id, observed 2026-05-21T22:30:44.124428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T22:26:03.786045Z digest=sha256:a108d284824ee60f08061a9868bec5a6e49e8db474eb7db996d9d09fb37c6fd6

Observation 702dc282-df19-4acd-8229-e890b72aa413 · inbound

Fast-SAM3D: 3Dfy Anything in Images but Faster cites this paper.

Fast-SAM3D: 3Dfy Anything in Images but Faster From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 2

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no resolver link, observed 2026-08-03T04:22:47.610803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T04:22:47.610803Z digest=sha256:438e34d8643137548c6843060a4a525587ffab888bf5bd4e883954b2a44e49f6

Observation 78db7401-7835-48d4-a34e-a0951a1f9590 · inbound

World Action Models are Zero-shot Policies cites this paper.

World Action Models are Zero-shot Policies From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 68

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verified exact
arxiv_id, observed 2026-05-11T16:18:15.481810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T16:18:15.003371Z digest=sha256:873aa188ae000434fd8b55980c6a73e7c0a154686cb431cb386d0bc17b573455

Observation c1fd5d38-b7a4-4086-855d-4b5fd94e95d4 · inbound

DiffSparse: Accelerating Diffusion Transformers with Learned Token Sparsity cites this paper.

DiffSparse: Accelerating Diffusion Transformers with Learned Token Sparsity From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 9

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no resolver link, observed 2026-07-13T12:34:28.755596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T12:34:28.755596Z digest=sha256:5c8c054982f8463a53e3a20e0468c381e4ed11302222fb8926786306a5b1ce25

Observation 42551d4a-22b7-49cd-9fc3-8263bb0e79b3 · inbound

Beyond Few-Step Inference: Accelerating Video Diffusion Transformer Model Serving with Inter-Request Caching Reuse cites this paper.

Beyond Few-Step Inference: Accelerating Video Diffusion Transformer Model Serving with Inter-Request Caching Reuse From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 5

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verified exact
arxiv_id, observed 2026-05-10T23:50:56.179935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T18:50:20.499116Z digest=sha256:fabc163a2ae698bb3480c480698a2a4384f9dddd15cb36b5bdd1e1fd51ea17a7

Observation 4c5930a3-a57b-4162-84c9-f568d814af24 · inbound

DRIFT: Harnessing Inherent Fault Tolerance for Efficient and Reliable Diffusion Model Inference cites this paper.

DRIFT: Harnessing Inherent Fault Tolerance for Efficient and Reliable Diffusion Model Inference From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 36

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verified exact
arxiv_id, observed 2026-05-11T07:35:58.660071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T17:05:49.089468Z digest=sha256:eed8440d474523781b7c070ca474562a697212a482a34f2297900ad8483bcac1

Observation 3f6ef25c-e39a-4bd2-bb06-c9654286c533 · inbound

Training-free, Perceptually Consistent Low-Resolution Previews with High-Resolution Image for Efficient Workflows of Diffusion Models cites this paper.

Training-free, Perceptually Consistent Low-Resolution Previews with High-Resolution Image for Efficient Workflows of Diffusion Models From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 31

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verified exact
arxiv_id, observed 2026-05-11T06:31:02.566347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T17:36:00.206444Z digest=sha256:a19d284d8df694fbf0a7c9855275f14cc8148189207c79322d4896502988ccbf

Observation 9b0e533a-f799-453c-a8fa-33a2cc0a65eb · inbound

CoCoDiff: Optimizing Collective Communications for Distributed Diffusion Transformer Inference Under Ulysses Sequence Parallelism cites this paper.

CoCoDiff: Optimizing Collective Communications for Distributed Diffusion Transformer Inference Under Ulysses Sequence Parallelism From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 50

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verified exact
arxiv_id, observed 2026-05-10T10:24:20.620999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T10:23:19.236803Z digest=sha256:0db78c1583c715b3ec92e45ba8b3a3dc5b9cd1a0be7ff28ff805b942f3b74b99

Observation 6f3af851-a7d0-4e89-b664-c0491ef7974c · inbound

Efficient Video Diffusion Models: Advancements and Challenges cites this paper.

Efficient Video Diffusion Models: Advancements and Challenges From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 84

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verified exact
arxiv_id, observed 2026-05-10T09:03:25.755645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T08:28:29.706249Z digest=sha256:e23797500f726b0aa9f65a41fde26034fc589726621d7cd107d7fa904aa4fc9b

Observation 414fff9f-13a8-4a05-ac7a-4f393892e2a5 · inbound

LayerCache: Exploiting Layer-wise Velocity Heterogeneity for Efficient Flow Matching Inference cites this paper.

LayerCache: Exploiting Layer-wise Velocity Heterogeneity for Efficient Flow Matching Inference From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 15

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verified exact
arxiv_id, observed 2026-05-11T10:56:05.166400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T15:15:42.201352Z digest=sha256:71abc8a242f966bbc300a551ed1572b9ab025dd4b0ac37946bd7fb7cca111a79

Observation 43e9dfbb-dd47-4ff0-add7-c0fc131caf2c · inbound

Motion-Aware Caching for Efficient Autoregressive Video Generation cites this paper.

Motion-Aware Caching for Efficient Autoregressive Video Generation From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 21

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verified exact
arxiv_id, observed 2026-05-11T10:06:01.695155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7dbf68a4-0b9a-4043-8f39-5bcb49efbffa · inbound

Motion-Aware Caching for Efficient Autoregressive Video Generation cites this paper.

Motion-Aware Caching for Efficient Autoregressive Video Generation From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 34

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verified exact
arxiv_id, observed 2026-05-15T07:19:49.790547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T07:16:05.225105Z digest=sha256:cb64f04d6980d070a75d6888ae955fbd959090d562aac213dae8719494a7ca6d

Observation a018baec-2199-4f56-a139-5400c0babc33 · inbound

Dynamic Video Generation: Shaping Video Generation Across Time and Space cites this paper.

Dynamic Video Generation: Shaping Video Generation Across Time and Space From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 20

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verified exact
arxiv_id, observed 2026-05-21T05:43:58.825288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T05:42:41.925474Z digest=sha256:e0021ee315c624a12999e8038747b3b61ae522adb7774d645dacd72e0c91bb10

Observation 9c23e474-74c9-4403-a2ae-0f99b2a9f5b6 · inbound

RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models cites this paper.

RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 36

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verified exact
arxiv_id, observed 2026-06-29T19:43:54.738490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 31c24ccf-edec-42e1-acd0-8dfdb3ef1d8a · inbound

Budget-Constrained Step-Level Diffusion Caching cites this paper.

Budget-Constrained Step-Level Diffusion Caching From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 10

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verified exact
arxiv_id, observed 2026-07-03T14:28:31.566541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 26a6b0d1-9ff1-4e81-a81c-6a631e9b3d05 · inbound

ResilPhase: Plug-and-Play Phase Mapping and Noise-Resilient Macro-Trajectory Extrapolation for Diffusion Acceleration cites this paper.

ResilPhase: Plug-and-Play Phase Mapping and Noise-Resilient Macro-Trajectory Extrapolation for Diffusion Acceleration From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 72

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metadata mismatch
arxiv_id, observed 2026-07-04T13:39:50.672856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9bff2d94-b189-4da7-bd70-cdbcd8d2685b · inbound

LearniBridge: Learnable Calibration of Feature Caching for Diffusion Models Acceleration cites this paper.

LearniBridge: Learnable Calibration of Feature Caching for Diffusion Models Acceleration From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 1

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arxiv_id, observed 2026-07-04T13:29:51.852099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T05:09:50.887733Z digest=sha256:e399c8ca79119977f99f0748e14f69b3f9cbc482c2e717c0fc04c2dfa75c47bb

Observation 322df4c4-7459-4b74-b4fa-dafaa3d76407 · inbound

OTCache: Optimal Transport for Geometry-Aware Caching in Diffusion Models cites this paper.

OTCache: Optimal Transport for Geometry-Aware Caching in Diffusion Models From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 25

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metadata mismatch
arxiv_id, observed 2026-07-01T09:45:39.548917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9b89574c-9e9e-4393-b5f3-490b22015e92 · inbound

ACID: Adaptive Caching for vIDeo generation cites this paper.

ACID: Adaptive Caching for vIDeo generation From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 42

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no resolver link, observed 2026-08-02T06:40:19.546870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T06:40:19.546870Z digest=sha256:df6d87aa708c625a2654543ebfc565c19ed1ae0fa55fa44fc3fb3513908b25c7

Observation 0d741a96-6ae5-47fe-80ef-0fd3ad9a44f6 · inbound

CODA: Algorithm-Hardware Co-design for Edge Video Diffusion via NMP-Enabled Compute-Cache Operator Disaggregation cites this paper.

CODA: Algorithm-Hardware Co-design for Edge Video Diffusion via NMP-Enabled Compute-Cache Operator Disaggregation From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 43

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no resolver link, observed 2026-08-02T00:49:38.216078Z

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Unavailable: canonical work link unavailable.

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Observation 3b84851b-9f73-4e9d-a4ba-60fbd5dac9a0 · inbound

DiTango: Cost-Effective Parallel Diffusion Generation with Selective Attention State Reuse cites this paper.

DiTango: Cost-Effective Parallel Diffusion Generation with Selective Attention State Reuse From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 18

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no resolver link, observed 2026-08-01T22:45:26.772478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation af3a0e18-3b64-4a10-86a4-00bae41edc90 · inbound

JAGG: Jacobian-Aggregated Group Gradient for Efficient GRPO Training of Diffusion Models cites this paper.

JAGG: Jacobian-Aggregated Group Gradient for Efficient GRPO Training of Diffusion Models From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 72

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no resolver link, observed 2026-08-01T17:41:00.897682Z

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Unavailable: canonical work link unavailable.

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Observation 5f4c57c8-5f8d-478d-bd4e-cf050ca036f8 · inbound

OmniCache: Multidimensional Hierarchical Feature Caching For Diffusion Models cites this paper.

OmniCache: Multidimensional Hierarchical Feature Caching For Diffusion Models From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Reference 20

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no resolver link, observed 2026-07-30T10:48:14.801997Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T10:48:14.801997Z digest=sha256:203036650cd7cf6c997be9af51eada8976125392f2aedf7cb8740f3ea4ef87aa