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Paper Citation Record · LEDGER

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving

As of 20 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 5 inbound Pith citation observations for arXiv:2506.13497.

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

pith.paper-citation-record.v1
2506.13497 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:05:06.570203Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:50:05.685350Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T22:21:18.726162Z

Reference resolution

57 of 57 outbound references displayed

  • verified exact0
  • verified fuzzy18
  • unresolved38
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c09a5e5e-d814-4ed1-ab2f-5e7d317a18d1 · outbound

This paper cites Deepspeed-inference: enabling efficient inference of transformer models at unprecedented scale.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Deepspeed-inference: enabling efficient inference of transformer models at unprecedented scale

Reference 1

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raw_fallback, observed 2026-08-15T20:05:07.270814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.255892Z digest=sha256:770518f6e05de3361a5d298c7ddcd4fabb5db24a067b0a3145131dbc63f1264a

Observation 94aae542-5cd2-4d01-806a-9ebb3ebd61f7 · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 2

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T20:05:06.261017Z digest=sha256:08ce94b02e02919c8f11842e84d225bbfc357f173fb0ffa9ba09c1dd6f45912a

Observation 828659ad-2bf4-48ac-892d-6e32b7519cd2 · outbound

This paper cites Striped Attention: Faster Ring Attention for Causal Transformers.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Striped Attention: Faster Ring Attention for Causal Transformers

Reference 3

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source=pdf_text observed=2026-08-15T20:05:06.265472Z digest=sha256:ca013a18f716dcb6707eceabe6bc0a9a266fc81ff364b2113d488da9dc4f3a63

Observation b4a73874-3515-4696-8bcb-5fe23b0f43b8 · outbound

This paper cites Pixart- 𝑠𝑖𝑔𝑚𝑎: Weak-to-strong training of diffusion transformer for 4k text- to-image generation.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Pixart- 𝑠𝑖𝑔𝑚𝑎: Weak-to-strong training of diffusion transformer for 4k text- to-image generation

Reference 4

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raw_fallback, observed 2026-08-15T20:05:07.257922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.270988Z digest=sha256:1af84f4a424db694965ab7dd59d301c85a2ebdae1e562630e6a504384bc83c9c

Observation a7ae735a-73f9-4479-b255-dcd01a0bd2da · outbound

This paper cites $\Delta$-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving $\Delta$-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers

Reference 5

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T20:05:06.275248Z digest=sha256:65ac87ab9ffa667a63ec2b124c2863e5e3a59e5db1bb1204a3567bfe2e266646

Observation 7cab8db1-c386-4cdb-b789-a0f4acde07f1 · outbound

This paper cites Flashattention: Fast and memory-efficient exact attention with io- awareness.Advances in Neural Information Processing Systems, 2022.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Flashattention: Fast and memory-efficient exact attention with io- awareness.Advances in Neural Information Processing Systems, 2022

Reference 6

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raw_fallback, observed 2026-08-15T20:05:07.245832Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T20:05:06.279204Z digest=sha256:3f0a9088ac606ebc603a105102385896d82308d241cdb64df3385083d9117457

Observation 5e3a6cfc-2a7f-4aa2-b222-41677c3b4395 · outbound

This paper cites Addison-Wesley, 2013.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Addison-Wesley, 2013

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.283294Z digest=sha256:958496895342d15840e120d5f174da8b493c7cbd4c664b3a1dfd290e1d6e4c81

Observation 3bcb97a0-d7f1-4d54-ae57-efeb117cd17d · outbound

This paper cites xDiT: an Inference Engine for Diffusion Transformers (DiTs) with Massive Parallelism.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving xDiT: an Inference Engine for Diffusion Transformers (DiTs) with Massive Parallelism

Reference 8

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source=pdf_text observed=2026-08-15T20:05:06.314626Z digest=sha256:336db9226143f2fdbbfa9a8a9a319ebd5818073fb3cff1c271437b325dcb929a

Observation 86101e07-82d0-46b6-b1c6-95170c33cf35 · outbound

This paper cites an unresolved cited work.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Unresolved cited work

Reference 9

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source=pdf_text observed=2026-08-15T20:05:06.373071Z digest=sha256:e2ecfed49e2f990423ad2e781ba2ec8f04e7584b38eaed24ce68958ba39f8317

Observation 7e27dc85-5be4-44fe-a8a1-c201f82d6e72 · outbound

This paper cites Reevaluating amdahl’s law.Communications of the ACM, 31(5):532–533, 1988.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Reevaluating amdahl’s law.Communications of the ACM, 31(5):532–533, 1988

Reference 10

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raw_fallback, observed 2026-08-15T20:05:07.209870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.383705Z digest=sha256:69c4170b4d246361d236cfd4870c1d83725d6014d4774e91cee1fdfbadd170eb

Observation f3d74ff0-29ce-44d0-b1ef-37740abf3c8b · outbound

This paper cites Denoising diffusion prob- abilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Denoising diffusion prob- abilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 11

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source=pdf_text observed=2026-08-15T20:05:06.388256Z digest=sha256:fa9b2430c36ff6ef44043996350edda50894f069d053d0cb379b0fd63d8fbb86

Observation 1d89c164-e0b3-46e0-992b-f5fc0d686405 · outbound

This paper cites FlashDecoding++: Faster Large Language Model Inference on GPUs.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving FlashDecoding++: Faster Large Language Model Inference on GPUs

Reference 12

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source=pdf_text observed=2026-08-15T20:05:06.391434Z digest=sha256:05dc142f6895523d669fd07727f93544db21b0ee87274d01021712834452ac96

Observation 2e0ac90f-a911-4c1e-95cc-3e0b02964cc2 · outbound

This paper cites an unresolved cited work.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Unresolved cited work

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.395037Z digest=sha256:e8ef9183212c614aeeee6c001ee8132e2bab9e5a42f9b75f47b7195dc4bef1da

Observation e05d157c-4b43-483b-9d7f-2d1f0c8fb6e7 · outbound

This paper cites an unresolved cited work.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Unresolved cited work

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.399663Z digest=sha256:658807419aeb95781f392d943541903f7c2d3279dfbaa1c1ad4fc96a81f88fa2

Observation 2b28b665-4e13-4260-b651-c556cecf1b01 · outbound

This paper cites MemServe: Context Caching for Disaggregated LLM Serving with Elastic Memory Pool.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving MemServe: Context Caching for Disaggregated LLM Serving with Elastic Memory Pool

Reference 15

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source=pdf_text observed=2026-08-15T20:05:06.403634Z digest=sha256:5cf2023b284e1c54c46e33d4963e973edac45b29301e985fa42a0e0fb026d7fc

Observation a1981db8-ea96-454b-9268-7f2ef1bc6c00 · outbound

This paper cites Inference without Interference: Disaggregate LLM Inference for Mixed Downstream Workloads.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Inference without Interference: Disaggregate LLM Inference for Mixed Downstream Workloads

Reference 16

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source=pdf_text observed=2026-08-15T20:05:06.408108Z digest=sha256:a2f7840010eff79f46c208e9f56251d906d82af76666812d1213e5f0ae7d5845

Observation fbe8a1b0-52fe-455c-a9ed-96937d17beb7 · outbound

This paper cites Reducing activation recomputation in large transformer models.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Reducing activation recomputation in large transformer models

Reference 17

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source=pdf_text observed=2026-08-15T20:05:06.412347Z digest=sha256:098addd87b52199971502479093cf9d06814e2e4927b5b4c6c6f9859bbb2f109

Observation a7303ded-12f3-40b5-8960-706a99dd863c · outbound

This paper cites an unresolved cited work.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Unresolved cited work

Reference 18

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.416218Z digest=sha256:cc30f788d4919cd773dd34542c18798aa922f60a845b077b9b32ca1b357c0a35

Observation 09665ae3-4dec-4ee0-8318-85a5adf32044 · outbound

This paper cites Efficient memory management for large language model serving with pagedattention.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Efficient memory management for large language model serving with pagedattention

Reference 19

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source=pdf_text observed=2026-08-15T20:05:06.420247Z digest=sha256:f9cbf7708638d9f5900e078c03ada2d48b9bc6e0b7b24fa02c1f0af54298c2b2

Observation 952f23a5-0eba-4af8-bb54-21dd21d43d11 · outbound

This paper cites Distrifusion: Distributed parallel inference for high-resolution diffusion models.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Distrifusion: Distributed parallel inference for high-resolution diffusion models

Reference 20

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source=pdf_text observed=2026-08-15T20:05:06.423782Z digest=sha256:458a525c35202075bcf8dd17de6c97c6326aec7a636f59b6690d68f571cb182c

Observation a0c45c94-03ed-4298-807c-f99269844f3c · outbound

This paper cites Sequence Parallelism: Long Sequence Training from System Perspective.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Sequence Parallelism: Long Sequence Training from System Perspective

Reference 21

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source=pdf_text observed=2026-08-15T20:05:06.427406Z digest=sha256:7607b25ec8bda8c10c3154f253c35af269fcd25f17193df8ef1c84c21f779e52

Observation 776d4615-57c6-40fd-a9f9-3beffd53da02 · outbound

This paper cites SwiftDiffusion: Efficient Diffusion Model Serving with Add-on Modules.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving SwiftDiffusion: Efficient Diffusion Model Serving with Add-on Modules

Reference 22

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source=pdf_text observed=2026-08-15T20:05:06.431371Z digest=sha256:14a07db51522cff7d481dcfc5f10a9cc18ec281997a5e83d3c42a4397acbe01e

Observation af10252a-5900-40b1-89c2-42ca4bdd52ce · outbound

This paper cites A survey of convolutional neural networks: analysis, applications, and prospects.IEEE transactions on neural networks and learning systems, 33(12):6999–7019, 2021.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving A survey of convolutional neural networks: analysis, applications, and prospects.IEEE transactions on neural networks and learning systems, 33(12):6999–7019, 2021

Reference 23

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source=pdf_text observed=2026-08-15T20:05:06.435356Z digest=sha256:9b05973272bfdedc61a9755ee090fe294e55fa07feb52ce32f5e13c0c84f71fc

Observation 0dd30c49-bbdd-4909-b771-32f1353fb0bb · outbound

This paper cites Train big, then compress: Rethinking model size for efficient training and inference of transformers.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Train big, then compress: Rethinking model size for efficient training and inference of transformers

Reference 24

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.439215Z digest=sha256:06807ab3207fb49ce69803f732a58adb3bea2ca237955dddb59ffd2354006786

Observation a6432ccc-f1db-4715-9c72-16c4fe52b485 · outbound

This paper cites Open-Sora Plan: Open-Source Large Video Generation Model.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Open-Sora Plan: Open-Source Large Video Generation Model

Reference 25

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source=pdf_text observed=2026-08-15T20:05:06.442913Z digest=sha256:59b158038818a45508071735b8c9acf9f727fbbb894dab98f28ce640c5d261cb

Observation 450a7e55-a72c-4049-af69-f0861dc39779 · outbound

This paper cites Ring Attention with Blockwise Transformers for Near-Infinite Context.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Ring Attention with Blockwise Transformers for Near-Infinite Context

Reference 26

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source=pdf_text observed=2026-08-15T20:05:06.446955Z digest=sha256:c2743ef255a0853c6784d8c51f5bbfe123f406e064fa121180730149c6e44487

Observation 8eb1b57e-b2f9-4a53-ace4-a9aca481b5de · outbound

This paper cites Deepcache: Accelerat- ing diffusion models for free.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Deepcache: Accelerat- ing diffusion models for free

Reference 27

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raw_fallback, observed 2026-08-15T20:05:07.115490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.451188Z digest=sha256:5198e12a74c575f7789161351510ab926d564f04f34eac0e37cc21798be84a33

Observation fd8191b9-2d46-4a62-8345-626b778740f3 · outbound

This paper cites Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models

Reference 28

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source=pdf_text observed=2026-08-15T20:05:06.454723Z digest=sha256:9d35c4caa4c18e1d7b1f272280e97c14bed18c1180c3988a05824bb9e5b45c26

Observation ef0325db-7c96-4ea0-9f29-35f78e5c1ded · outbound

This paper cites The design process for google’s training chips: Tpuv2 and tpuv3.IEEE Micro, 41(2):56–63, 2021.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving The design process for google’s training chips: Tpuv2 and tpuv3.IEEE Micro, 41(2):56–63, 2021

Reference 29

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raw_fallback, observed 2026-08-15T20:05:07.103618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.459888Z digest=sha256:623542e7c315a3fffa448e2496f3b43faba0b7308e9579f472ca36675518f617

Observation 7d4bd50a-5f2c-499d-8c1b-33771e994039 · outbound

This paper cites NCCL.https://docs.nvidia.com/deeplearning/nccl/user- guide/docs/overview.html.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving NCCL.https://docs.nvidia.com/deeplearning/nccl/user- guide/docs/overview.html

Reference 30

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raw_fallback, observed 2026-08-15T20:05:07.090777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.464126Z digest=sha256:35fd11f2922d6b31d1aa35303fffbebe31a9906fd07894225ce3174f5e5d9479

Observation 9c56a28e-6aa1-4617-a7a0-e656c98e93d8 · outbound

This paper cites an unresolved cited work.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Unresolved cited work

Reference 31

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.468166Z digest=sha256:d1191c8a1a3501edb3ec6663ad17306df39e47fc3b7b6a61dc2e067845a9e6fc

Observation 515dfd6f-029b-4467-b878-13b93cd913bc · outbound

This paper cites Splitwise: Efficient generative LLM inference using phase splitting.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Splitwise: Efficient generative LLM inference using phase splitting

Reference 32

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Observation f976183c-5317-4335-985d-282c1099f744 · outbound

This paper cites Scalable diffusion models with transformers.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Scalable diffusion models with transformers

Reference 33

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source=pdf_text observed=2026-08-15T20:05:06.476265Z digest=sha256:b3e6866ca15b700767ee14a3512f92b899ef2599f5c885d998431ead72837a95

Observation 42600dd4-2549-455e-96b7-992e377d7a46 · outbound

This paper cites Variational autoencoder.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Variational autoencoder

Reference 34

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raw_fallback, observed 2026-08-15T20:05:07.057332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.480002Z digest=sha256:99c9cb2406e4036ad4f5c325be7a025cd4be009d0b8af592c55bcf1f675f98d3

Observation 809ed3dd-6705-4ed1-9ba5-c7688ce26c2f · outbound

This paper cites Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation

Reference 35

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no resolver link, observed 2026-08-15T20:05:06.483437Z

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source=pdf_text observed=2026-08-15T20:05:06.483437Z digest=sha256:c8288e4257e5146d53348707f6f2b1874b7a820b9443d1448b42d05d413f9442

Observation fc481b10-0b48-4be1-a105-321f9ce13c9c · outbound

This paper cites A remark on stirling’s formula.The American mathematical monthly, 62(1):26–29, 1955.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving A remark on stirling’s formula.The American mathematical monthly, 62(1):26–29, 1955

Reference 36

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.486911Z digest=sha256:ec57cc86ef5f19e8576ea88ef5d9d1721d9b0cda40e6622620735e8f62a49bec

Observation ae3ab585-60f0-4e23-aab9-ff770706ee90 · outbound

This paper cites an unresolved cited work.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Unresolved cited work

Reference 37

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raw_fallback, observed 2026-08-15T20:05:07.031371Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.490338Z digest=sha256:ab1dee45e3cccc201c29fab3b0f3d237cbaaae0c4442d94d88c0338ac6c0a2fc

Observation d853f804-380e-479a-837c-d3899bdeed23 · outbound

This paper cites FORA: Fast-Forward Caching in Diffusion Transformer Acceleration.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving FORA: Fast-Forward Caching in Diffusion Transformer Acceleration

Reference 38

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source=pdf_text observed=2026-08-15T20:05:06.493639Z digest=sha256:d640d05c5cdefcfc2657d86033fa5e4a3ea063a249839dcab947d427cf43e79c

Observation 9717fb87-54e7-4425-84f3-b90446bb1b6e · outbound

This paper cites Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 39

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source=pdf_text observed=2026-08-15T20:05:06.496920Z digest=sha256:9725026beca9714616808ec308bacc0e44083a8aac19bfd95f49b83d29068dc6

Observation 99f9ae0c-df2e-46f9-8b48-d7b9731a8442 · outbound

This paper cites Fundamentals of queueing theory, volume 399.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Fundamentals of queueing theory, volume 399

Reference 40

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raw_fallback, observed 2026-08-15T20:05:07.019142Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.500900Z digest=sha256:6e16050916b25a82a91d57b78c2cc0249403e7f46fbb0c5756385d10ae23d971

Observation 5e8346e6-8498-41a0-9e8f-2e61557b7111 · outbound

This paper cites Rpc: Remote procedure call protocol specification version 2.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Rpc: Remote procedure call protocol specification version 2

Reference 41

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raw_fallback, observed 2026-08-15T20:05:07.005583Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.504641Z digest=sha256:dac13cf21d30b76a5f508d459ef621936721a04ab405e6ed96f002c81d15fd75

Observation 39163bc3-5ad0-4b37-af08-44df92dbeaea · outbound

This paper cites One Embedder, Any Task: Instruction-Finetuned Text Embeddings.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving One Embedder, Any Task: Instruction-Finetuned Text Embeddings

Reference 42

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no resolver link, observed 2026-08-15T20:05:06.508413Z

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source=pdf_text observed=2026-08-15T20:05:06.508413Z digest=sha256:c14bcffda1e860a106a8ec5115146078169105e59cdd52a90471b5a8c38bdc7b

Observation 1f8c96ef-7309-463a-a795-4d3ed50d2009 · outbound

This paper cites Videosys: An easy and efficient system for video generation, 2024.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Videosys: An easy and efficient system for video generation, 2024

Reference 43

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raw_fallback, observed 2026-08-15T20:05:06.989202Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.512520Z digest=sha256:08f02ce5ca4dff63d6271db4b4db266f5b6c273bcef7561de6c1bf3d0fad8fcc

Observation f28349fa-4562-4a07-8c44-ed35d4692974 · outbound

This paper cites New and old results for the m/d/c queue.AEU- International Journal of Electronics and Communications, 60(2):125–130, 2006.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving New and old results for the m/d/c queue.AEU- International Journal of Electronics and Communications, 60(2):125–130, 2006

Reference 44

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raw_fallback, observed 2026-08-15T20:05:06.975467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.516173Z digest=sha256:74ecdee1b7f4dbeda580ebb45c25c05a07d85272004038e6f75c0e42d160faf8

Observation 3ceda22f-ceb0-4af3-a2cf-929ddfc0923d · outbound

This paper cites PipeFusion: Patch-level Pipeline Parallelism for Diffusion Transformers Inference.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving PipeFusion: Patch-level Pipeline Parallelism for Diffusion Transformers Inference

Reference 45

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source=pdf_text observed=2026-08-15T20:05:06.519810Z digest=sha256:88df349dc5c31e91f046fffd102c2324963fbc21a98c9cc1bb0eb707e3f69b3a

Observation 4a57b75d-e3bb-4783-8b24-1a5b2f3cb3ec · outbound

This paper cites NVLink.https://en.wikipedia.org/wiki/NVLink.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving NVLink.https://en.wikipedia.org/wiki/NVLink

Reference 46

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raw_fallback, observed 2026-08-15T20:05:06.960296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.523938Z digest=sha256:9b61dd6c33903a9e710c2a1e2ccf8053ef6419610ef8b033a340832343c4b366

Observation 293b7419-54dd-475d-89be-088c6e2838c9 · outbound

This paper cites Cache me if you can: Accelerating diffusion models through block caching.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Cache me if you can: Accelerating diffusion models through block caching

Reference 47

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source=pdf_text observed=2026-08-15T20:05:06.527751Z digest=sha256:85076b7514f402ed914cccf6c911ff13fc05556ca2be692a522997e749f54e9c

Observation 63df851d-b387-463a-8250-45dd56ba37ea · outbound

This paper cites Preact: Predictive resource allocation for bursty workloads in a co-located data center.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Preact: Predictive resource allocation for bursty workloads in a co-located data center

Reference 48

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raw_fallback, observed 2026-08-15T20:05:06.939121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.531612Z digest=sha256:1638630bd32932ebea978d4c56e89ceab8b59dbc16ffd4ac5f4ed236033802bb

Observation 46ae53c2-2565-4ed4-b3ec-0021dd8296f1 · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 49

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source=pdf_text observed=2026-08-15T20:05:06.535684Z digest=sha256:8a541cad42c4ccade2ba1c9a992813d460fbdb1bee975a5197241f547d5d2eb2

Observation eafb86e6-4a05-45d1-8638-5eafa4f9a10f · outbound

This paper cites Orca: A distributed serving system for {Transformer-Based} generative models.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Orca: A distributed serving system for {Transformer-Based} generative models

Reference 50

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raw_fallback, observed 2026-08-15T20:05:06.923834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T20:05:06.540557Z digest=sha256:c1d00297752b94ee3d810df2209d14563326dbcf91f48cf8a0304f0aa1699a64

Observation a9393754-35b7-4b19-b409-61a895cd667a · outbound

This paper cites DiTFastAttn: Attention Compression for Diffusion Transformer Models.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving DiTFastAttn: Attention Compression for Diffusion Transformer Models

Reference 51

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source=pdf_text observed=2026-08-15T20:05:06.545013Z digest=sha256:d207a1da39089af0912837708c84c36ce9863c5b43d923ddc161c328aad3e770

Observation 9bf367cf-2d7e-4562-965a-12c78c0ebb7c · outbound

This paper cites Faster Diffusion via Temporal Attention Decomposition.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Faster Diffusion via Temporal Attention Decomposition

Reference 52

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source=pdf_text observed=2026-08-15T20:05:06.549223Z digest=sha256:5689138e9a4327680a12af552ef6f91a122ca13cbecbbd897c53f2898548fde0

Observation 3c7775af-a8e7-4625-ad2d-14f2edcf4b52 · outbound

This paper cites DSP: Dynamic Sequence Parallelism for Multi-Dimensional Transformers.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving DSP: Dynamic Sequence Parallelism for Multi-Dimensional Transformers

Reference 53

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source=pdf_text observed=2026-08-15T20:05:06.553354Z digest=sha256:04692779b91a915af02bce0382c97641577a9bcdab78b887d1d49c6e9d6d5da3

Observation 84245383-cba9-4a01-a43b-05d640fb7874 · outbound

This paper cites Real-Time Video Generation with Pyramid Attention Broadcast.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Real-Time Video Generation with Pyramid Attention Broadcast

Reference 54

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source=pdf_text observed=2026-08-15T20:05:06.557898Z digest=sha256:469b976686d3201f1e475b6c6124c745c610cde098ad424131708ca6f880fa3f

Observation 2103e915-1e4a-4c46-ab00-cf103ed9f552 · outbound

This paper cites Open-sora: Democratizing efficient video production for all, March 2024.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Open-sora: Democratizing efficient video production for all, March 2024

Reference 55

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source=pdf_text observed=2026-08-15T20:05:06.562133Z digest=sha256:e390d3389fd6f3dc508af85f4080674d929777fcb8b49757624c72258673131c

Observation 8f99295a-6bb4-48b5-9981-c6af53d2edc7 · outbound

This paper cites Open-Sora: Democratizing Efficient Video Production for All.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving Open-Sora: Democratizing Efficient Video Production for All

Reference 56

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no resolver link, observed 2026-08-15T20:05:06.565942Z

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source=pdf_text observed=2026-08-15T20:05:06.565942Z digest=sha256:0f946df3c99fb8edc52967175759def1b579d69c3298e38589d2c3ec58ba1705

Observation 11ed2b9a-3168-48be-a6e4-6bc18ce08a01 · outbound

This paper cites DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving.

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving

Reference 57

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no resolver link, observed 2026-08-15T20:05:06.570203Z

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source=pdf_text observed=2026-08-15T20:05:06.570203Z digest=sha256:eef76b35dc6919f08907645f551513f488098e7922d7e181b891edba331f06e5

Pith citing papers

Observation 9a2ef9ec-b0c1-4e4e-a98b-33d034fd302d · inbound

TetriServe: Efficiently Serving Mixed DiT Workloads cites this paper.

TetriServe: Efficiently Serving Mixed DiT Workloads DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving

Reference 2025

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source=pdf_text observed=2026-08-04T12:55:10.421426Z digest=sha256:46f3b7dff19ddb16acf5c2326a63e6b96f11b7627436b6077af1d2db40417416

Observation f6f3628e-fe3b-432f-b7ef-a3c3167ffe19 · inbound

Cornfigurator: Automated Planning for Any-to-Any Multimodal Model Serving cites this paper.

Cornfigurator: Automated Planning for Any-to-Any Multimodal Model Serving DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving

Reference 16

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arxiv_id, observed 2026-05-16T22:21:18.728402Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-16T22:20:48.239186Z digest=sha256:e046fbdc1b4e560ad09a409b65ec1193eb459e5fd21f297d0e0a47a3c696573c

Observation 1b0d1033-9fa6-4c35-ade5-39a3c39b7347 · inbound

TempoNet: Slack-Quantized Transformer-Guided Reinforcement Scheduler for Adaptive Deadline-Centric Real-Time Dispatchs cites this paper.

TempoNet: Slack-Quantized Transformer-Guided Reinforcement Scheduler for Adaptive Deadline-Centric Real-Time Dispatchs DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving

Reference 40

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arxiv_id, observed 2026-05-15T21:11:37.593778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-15T21:11:07.026338Z digest=sha256:eb48efb1a3adb496f248d73f4eac519d3fe701769017a12e649cff9ee342678b

Observation 4bbc630b-c53c-4645-aa4b-496032172d23 · inbound

GENSERVE: Efficient Co-Serving of Heterogeneous Diffusion Model Workloads cites this paper.

GENSERVE: Efficient Co-Serving of Heterogeneous Diffusion Model Workloads DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving

Reference 15

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verified exact
arxiv_id, observed 2026-05-10T22:00:47.892092Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T20:22:20.395250Z digest=sha256:6cfa29b2bf44260d8fdf6afaf496ef00b98e48ed2eeda8d023b2daa306d1e518

Observation b65cc737-39d8-4e89-85c3-5b3c43cb3795 · inbound

OpScale: Operator-level Provisioning and Autoscaling for LLM Serving cites this paper.

OpScale: Operator-level Provisioning and Autoscaling for LLM Serving DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T05:50:05.685350Z digest=sha256:176d3f0c9e28eeac0030c7ded2f2a8829faf9ab7ce4829f649d669ce4af41d1e