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Paper Citation Record · LEDGER

DDiT: Dynamic Resource Allocation for Diffusion Transformer Model Serving

As of 18 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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.255892Z digest=sha256:fa472121583b994a8043bad8ef68b907036e2c651f12bbf738931e71c16c391f

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:b5c54c7893d889ce6f2426090033ed0e98294575a31b5579fa286e6b85a9a716

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=sha256:581e6d2496f89c48d74f4e2bc6a5b14a541fdcf8c68d11223c02ea512b4861aa

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.270988Z digest=sha256:aa5bd18e11dd2d62d22e1a5de22d737d4fae75d03524734c3f202c8aee26ec56

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=pdf_text observed=2026-08-15T20:05:06.275248Z digest=sha256:70b605d5bf7813ad4bd09851db50c4f35572d06a0031ab0a032ceca1c16679de

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=sha256:329715aefeb6d506d1f826736614d76071707640ca9ffd81b148e9a04114f045

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.283294Z digest=sha256:684411146251069e167dc63e482930b0279b688868d18788dbeac01d03a0a3ed

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=sha256:964dcf4a2d96dd0fd5dfb127376a41fea741f963b6ba3886154d8544ff3a0db4

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:d57dc44c0144e0375cf6b499530d16d0daa358599197009bc64254ad71c74bdc

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.383705Z digest=sha256:d062becadbcd5d9914849407f9e39e8a017100d2d2da4f88d423d3ff37f43f56

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=sha256:23fc5c434c09b78cbb8e140b6ed2b9899d9be2f7cb7912bc31bb9afed16445f6

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=sha256:00c466c2153e3fa2708af62d90ecaf520542e2b4e6db7689de88078781e21d19

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.395037Z digest=sha256:63d3ab179194f6d155b5fed1adc3bca2698f5dffe31aefa11c538b9a14bd0cc5

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.399663Z digest=sha256:0e518094508f004b0f4c179d486f387464a46618817f4e8bd0e630a0defba765

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:a37cdceace576aa961f0e59d07d1a44c74ff4b626dd75b228b5454e14dc0ef98

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=sha256:9ff3bf53a814f9e24d5b0510b2494c313486a07d4a3e15a311dc1dc934de99c9

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:e61f5069585a42374f5d473890193e6499e972facae82823d1cb425eb5943d49

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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source=pdf_text observed=2026-08-15T20:05:06.416218Z digest=sha256:670282966fc9d9f1ea5dc3c2dc5c8929485bdeceff0b4e4090ccb228fdef43fb

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:ce2cddb2f8637241e85919fc615b55ebac8bfe22fceda45dfa98fce091da44c1

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:ffd4695f1e735fb144c5ad9540576dc82b826ca7e1a172366038fc167ef14b73

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=sha256:43608615110d22b4f0be58ceb3a67f13a30b8e07f219520aa525c2635d7f2546

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=sha256:4d5c9dd43ff07cfecbdf7600f77b29395f074b0e84a3e9168cd7a0bda9c75364

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:f4c16b701238fcc3c69c009fb4997d137f14f95c707e3a254c2bf2eadaa0b2bd

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.439215Z digest=sha256:caad5d228da4592a77b24d7c32554b13843dbb7e858a92286ca105c7a9046978

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:ca478d484bf66df2ea897016bf06bf668409fd528d44601cb22b4cae5d881023

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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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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.451188Z digest=sha256:7969354386344e5dfefabc36833d53edb0b7f2b64616fa8dd324fe1d2d8e3192

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=sha256:903b5e9be75da5b0769b2ccb90e34bd577af2fdd156db4494059c0d5f016070d

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.459888Z digest=sha256:fb6422b0958782bbaf29502d202004ae0d467cab0b556bb5a9647cbe6da537ea

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.464126Z digest=sha256:95d7527c52ff254b20ab81de79e2c80d0b9741133ee13da9a90c950bfed39ff5

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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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:bb820a588ad0e9786728690e90c92842c67a328603f2f451899acbf78ef429fb

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.480002Z digest=sha256:2e85b79b3001c15da159bf0830a0a74fc549da7afee6fb484d84dc1bf03a4751

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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source=pdf_text observed=2026-08-15T20:05:06.483437Z digest=sha256:2b797e98a6eae30f5465f4e9ed2e7df53c93937c447551bfa800e60391431c27

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.486911Z digest=sha256:5a3c043d77d7f38311537de33c81cf76fcbb283935935d60c485a2b0d4910b44

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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source=pdf_text observed=2026-08-15T20:05:06.490338Z digest=sha256:2c13d9eacccb2b0d17a5285252b5620510bb6a4e57458f8f1f67381b13c908e6

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=sha256:2dbdc08549151074e3b57e1312765ee07156b221717c57d82cd3aa1d9a314ce2

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=sha256:0687a0ed5cfdfecdafb288da36d17b73a696eef8cda33b1d86cd454c07898947

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.500900Z digest=sha256:1cc092d5546ecd31ffb7b3b2b2005e402fb19819b70c375bbe1dd2dd261892ec

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.504641Z digest=sha256:83e212f3e1fa009e6dcea57eb52197c6dc863bccddd68fb3740c0b0fea59d904

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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source=pdf_text observed=2026-08-15T20:05:06.508413Z digest=sha256:b20059b03fa6b5700dbe14ab5d136c26b6e0aee8b09d8a853fc62a5a104840fe

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.512520Z digest=sha256:cad9c384e36f2dd0c1c94f0759918bcd4003cdc8173ff0029d64efa264eca818

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

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.516173Z digest=sha256:c16cd343a026d61941b6269446020af6029306c0113aa8fc4c0b5f3573ef31ad

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=sha256:21e5517db45f5c51decdd7762b3520d52be4234e364781f9ae4207a50094f89f

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.523938Z digest=sha256:e6321562b6260100064091a2e4899b61aada61ee7f2a77e00fa3cbb2e4f6f82c

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=sha256:7865c3cbf87ad0033ddce677da79ff863f358554ebe13f48e6c82640b832881c

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.531612Z digest=sha256:4e06fa004ecc3ce67accd92f63970ae8618bcedca288905d810ae15eb0d8650b

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:d74009d0d327f8a1fcf946cf6cb55ec56556fe133784a4a9882f17e06061f4f4

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T20:05:06.540557Z digest=sha256:8327da6c7b875595add6692b5a7bf36644fc81d29b0a616cc432aad1a343611a

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=sha256:1d3618e1d1631eb4e2248f467e524c59ba7bc871968a2054f17bf92967e08e79

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:af00931407c007f2afe19439efc12cc457d481fc474da4897abf84451873564f

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=sha256:4486f1442795b5c8893ac79d001aee4081444cba96932770f2652bbbb1b5b3a1

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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no resolver link, observed 2026-08-15T20:05:06.557898Z

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source=pdf_text observed=2026-08-15T20:05:06.557898Z digest=sha256:fcdc0890a020bf0cb1d4dc73121c6c2f1bc653a6d58e02883f7bc79b5e36b880

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:b59fcc2a6e6ec8d10e96306e4a401bf4ae56098ff4d291b825c6077ab786e541

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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source=pdf_text observed=2026-08-15T20:05:06.565942Z digest=sha256:3151595e50b4196a0e68b34d3256dc0340fdf7237576e4e556ad3bb15069d90e

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=sha256:61ce94291c44847f86f3d263fce8e08c9c276093bc9b61837995999b31fa77f3

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=sha256:21923d19e6038ecd01d2fe0b36998972c01270b59c88c4bfc137dc94c7b400cc

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-16T22:20:48.239186Z digest=sha256:57450f6ce11a457cec1fa06b926368eb9d33879ee52e8d3f8a4779a9b6e82fe3

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-15T21:11:07.026338Z digest=sha256:b78007ca36f26e9a2b339753811c7c1c0984fd6737ef0047258d5d270feed060

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T20:22:20.395250Z digest=sha256:d2f1dac7e42b1bb0e452ed58713a09211a549cf1596123860d43ad72e4d1b38d

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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source=pdf_text observed=2026-08-14T05:50:05.685350Z digest=sha256:7ba7589aee5f65d742fb53623cf7e62ef3d9b9c4eeae124ed621d08964cce534