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Paper Citation Record · LEDGER

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation

As of 9 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 0 inbound Pith citation observations for arXiv:2505.21817.

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

pith.paper-citation-record.v1
2505.21817 v1

Coverage vector

measured 72 of 72 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:26:46.404857Z

measured 72 of 72 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

72 of 72 outbound references displayed

  • verified exact0
  • verified fuzzy28
  • unresolved44
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ebb7c73b-37a0-4b0c-b08c-de36b836fdbc · outbound

This paper cites Generative modeling by estimating gradients of the data distribution.Advances in neural information processing systems, 32, 2019.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Generative modeling by estimating gradients of the data distribution.Advances in neural information processing systems, 32, 2019

Reference 1

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Observation 47e60767-e29c-4e00-9bfe-9deccde0c833 · outbound

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

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 2

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Observation 15667fbe-526b-4986-9d0e-a26e72bc61ec · outbound

This paper cites Score-based generative modeling through stochastic evolution equations in hilbert spaces.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Score-based generative modeling through stochastic evolution equations in hilbert spaces

Reference 3

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0477864e-820f-4f05-8928-0d81f33aec57 · outbound

This paper cites High- resolution image synthesis with latent diffusion models.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation High- resolution image synthesis with latent diffusion models

Reference 4

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source=pdf_text observed=2026-08-07T13:26:39.632477Z digest=sha256:cf17ca1e49dca51c67e6c5103b7a8de30f0e0cce2bb234abc2e7c54cd8b9cb2e

Observation 382cf3db-f595-4a4f-9aa2-cd478f96b434 · outbound

This paper cites SDXL: Improving latent diffusion models for high-resolution image synthesis.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation SDXL: Improving latent diffusion models for high-resolution image synthesis

Reference 5

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:39.718866Z digest=sha256:e54605afeddc8dd307955dbfa6812baf4a74e1eb8cffd75535ffad3a28b05a23

Observation 3f712b03-dd8a-410a-bc4b-e26fe0578efb · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 6

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source=pdf_text observed=2026-08-07T13:26:39.814870Z digest=sha256:39a500a95905c78ac607c7f9e9f8e8c3760be727c37426a6c79ae65daac2c00a

Observation e8d0d899-1654-40f8-89b3-f44ab5c667ea · outbound

This paper cites Scalable diffusion models with transformers.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Scalable diffusion models with transformers

Reference 7

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source=pdf_text observed=2026-08-07T13:26:39.894207Z digest=sha256:6e2d47c2875644dc48880a0b6321d92f63000a4d6e8fc008045aff8f7f654eac

Observation bb7aa4f2-ec75-4533-a964-745b85a23d92 · outbound

This paper cites Blended diffusion for text-driven editing of natural images.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Blended diffusion for text-driven editing of natural images

Reference 8

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source=pdf_text observed=2026-08-07T13:26:39.976839Z digest=sha256:2f4b4f6d865d578bca5b4500a5d2be5103f9af263d07e1cfa26071b9a28f4b74

Observation 847e32c3-307c-4347-ae3a-54e477577fd2 · outbound

This paper cites Imagic: Text-based real image editing with diffusion models.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Imagic: Text-based real image editing with diffusion models

Reference 9

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source=pdf_text observed=2026-08-07T13:26:40.113497Z digest=sha256:bf6f48f480c2d4786a84e69194ddd181db518ee2be4b28c8f5aabfe8e2f37d39

Observation 32e93927-d97b-4bab-b01f-9bd7d89833f6 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Adding conditional control to text-to-image diffusion models

Reference 10

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source=pdf_text observed=2026-08-07T13:26:40.223962Z digest=sha256:978571d4bf6c2b5f4c0b1afe9ae22474d6bd03b1f7e586531310d8aa067c9d9a

Observation 56abc617-50a0-4f55-8500-b87f517c8622 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 11

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source=pdf_text observed=2026-08-07T13:26:40.342405Z digest=sha256:dfa86290e8f38e32da348f39e5efdac03e9a017f94cdc40743d3b1caf5f1e61f

Observation 8fce975f-b20f-47fa-ab4b-6b599ae4314a · outbound

This paper cites Denoising Diffusion Implicit Models.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Denoising Diffusion Implicit Models

Reference 12

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source=pdf_text observed=2026-08-07T13:26:40.460387Z digest=sha256:f70bc07262f263adf41deeafbfafdafa35c3a2d188a477c527ca6169f7f66127

Observation eb9f4e96-8343-49c6-9861-32497dfb890a · outbound

This paper cites Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.Advances in Neural Information Processing Systems, 35:5775–5787, 2022.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.Advances in Neural Information Processing Systems, 35:5775–5787, 2022

Reference 13

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 102b7c40-23a5-4e3c-ab49-50265bdbf628 · outbound

This paper cites Consistency models, 2023.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Consistency models, 2023

Reference 14

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source=pdf_text observed=2026-08-07T13:26:40.664773Z digest=sha256:6352d6017fad812689e238e40f7d24f0a207bd0473d4eb706e824b7eeb003f82

Observation f37ca086-23be-45d6-93d6-ab7a4ce4c1f6 · outbound

This paper cites Progressive Distillation for Fast Sampling of Diffusion Models.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Progressive Distillation for Fast Sampling of Diffusion Models

Reference 15

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Observation 89041c26-b99f-409e-baae-26d3e6568102 · outbound

This paper cites Deepcache: Accelerating diffusion models for free.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Deepcache: Accelerating diffusion models for free

Reference 16

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source=pdf_text observed=2026-08-07T13:26:40.907726Z digest=sha256:7c10c28524a08146dcf92c75b68562245568307b050921ff874d58d74508f068

Observation 97b9aca5-a926-4063-848d-fefe4bc18a21 · outbound

This paper cites HeadRouter: A Training-free Image Editing Framework for MM-DiTs by Adaptively Routing Attention Heads.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation HeadRouter: A Training-free Image Editing Framework for MM-DiTs by Adaptively Routing Attention Heads

Reference 17

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Observation b84fff20-f9e3-4708-a47c-44be0b9a215a · outbound

This paper cites Not all prompts are made equal: Prompt-based pruning of text-to-image diffusion models.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Not all prompts are made equal: Prompt-based pruning of text-to-image diffusion models

Reference 18

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f3a1b19b-1510-4b34-9134-36fc12b41e62 · outbound

This paper cites LAPTOP-Diff: Layer Pruning and Normalized Distillation for Compressing Diffusion Models.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation LAPTOP-Diff: Layer Pruning and Normalized Distillation for Compressing Diffusion Models

Reference 19

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Observation eaaf00d3-4918-4f68-8ed6-9734ee39d3aa · outbound

This paper cites Ld-pruner: Effi- cient pruning of latent diffusion models using task-agnostic insights, 2024.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Ld-pruner: Effi- cient pruning of latent diffusion models using task-agnostic insights, 2024

Reference 20

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 7af81d95-063a-44b2-b2ac-73f2d245bf18 · outbound

This paper cites Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models, 2022.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models, 2022

Reference 21

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Observation b84d84f1-7988-4148-82d3-e8e08b32fa3d · outbound

This paper cites Pseudo numerical methods for diffusion models on manifolds.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Pseudo numerical methods for diffusion models on manifolds

Reference 22

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Observation 3fbe9389-487e-48e5-a7ce-aa50f37b70c9 · outbound

This paper cites Fast sampling of diffusion models with exponential integrator, 2023.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Fast sampling of diffusion models with exponential integrator, 2023

Reference 23

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Observation fbf973cf-9b4d-4a30-9252-a20d824b7906 · outbound

This paper cites Parallel sampling of diffusion models, 2023.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Parallel sampling of diffusion models, 2023

Reference 24

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source=pdf_text observed=2026-08-07T13:26:41.645514Z digest=sha256:6e74f5c434a7cea9a25e7775f51b861767366e140169edc5dde947e93136fab7

Observation cd04df2a-fc4c-4653-8e2d-a6ecc034c23a · outbound

This paper cites Latent consistency models: Synthesizing high-resolution images with few-step inference, 2023.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Latent consistency models: Synthesizing high-resolution images with few-step inference, 2023

Reference 25

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Observation bfee2a1a-56e7-4746-86bf-3527829c2e76 · outbound

This paper cites Kingma, Stefano Ermon, Jonathan Ho, and Tim Salimans.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Kingma, Stefano Ermon, Jonathan Ho, and Tim Salimans

Reference 26

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source=pdf_text observed=2026-08-07T13:26:41.827974Z digest=sha256:a4b8bbba51f6976421ecd7f3e62770a62c1c70a256064fb4df95504418a0102d

Observation 250259aa-cbb8-46f7-b2e2-c5f9261055c8 · outbound

This paper cites Adversarial diffusion distillation, 2023.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Adversarial diffusion distillation, 2023

Reference 27

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Observation f0e65431-ca3f-45b1-83e1-d2ea7fa8969b · outbound

This paper cites Tract: Denoising diffusion models with transitive closure time-distillation, 2023.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Tract: Denoising diffusion models with transitive closure time-distillation, 2023

Reference 28

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:42.045635Z digest=sha256:cd8e273804b2ccd5d91023ade3c738179f8ed6ab9e56547f6b98df3e1c35f803

Observation 08142e24-92d4-464d-89d3-4656676ee772 · outbound

This paper cites Accelerating diffusion models via early stop of the diffusion process, 2022.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Accelerating diffusion models via early stop of the diffusion process, 2022

Reference 29

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source=pdf_text observed=2026-08-07T13:26:42.137327Z digest=sha256:174f66ea3263b38c93690fc36a67ee016a27a2324e6ebe90de0961f6f82f54c0

Observation ac700851-392c-47ef-9d35-e19c9ecbde12 · outbound

This paper cites Dip-go: A diffusion pruner via few-step gradient optimization.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Dip-go: A diffusion pruner via few-step gradient optimization

Reference 30

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Observation 6f0766bd-10ef-4f34-ac5b-a0ebc69b27cd · outbound

This paper cites Faster diffusion: Rethinking the role of the encoder for diffusion model inference.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Faster diffusion: Rethinking the role of the encoder for diffusion model inference

Reference 31

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raw_fallback, observed 2026-08-07T13:26:49.868050Z

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=2026-08-07T13:26:42.322321Z digest=sha256:e687df23ccf22578c4b2ee3805258cf82877173046b02dfa9253e9a7948608fe

Observation f1e98ef5-f4ab-40db-a069-ea413c356a5b · outbound

This paper cites Learning-to-cache: Accelerating diffusion transformer via layer caching.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Learning-to-cache: Accelerating diffusion transformer via layer caching

Reference 32

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T13:26:42.435399Z digest=sha256:e94935cc948dcb5ea22ce3c2389cdfe1f01d165426f2f82c75316d5594328f8d

Observation 8785b09e-3769-4be6-9d8f-a110c73c3253 · outbound

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

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Cache me if you can: Accelerating diffusion models through block caching

Reference 33

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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=2026-08-07T13:26:42.523379Z digest=sha256:463da72a5c01768bbf2b0a854c76c8b1db6f0a3722d9721095b49c8f52352862

Observation dc9a15b4-d3d1-486a-953a-24ca2b48dea8 · outbound

This paper cites Post-training quantization on diffusion models.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Post-training quantization on diffusion models

Reference 34

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:42.648287Z digest=sha256:2446416d1af3f7901e33a8bca498d1649fa5f800ead71fc674562feea6588dfb

Observation b09d6fec-f3e5-433f-8ab9-4f348bb37650 · outbound

This paper cites Temporal dynamic quantization for diffusion models.Advances in neural information processing systems, 36:48686–48698, 2023.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Temporal dynamic quantization for diffusion models.Advances in neural information processing systems, 36:48686–48698, 2023

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-07T13:26:49.338591Z

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=2026-08-07T13:26:42.745729Z digest=sha256:b857e085f57e83e3adbfc101477cab9ddbcad8bbbd1ef3478cc4ede656895ac6

Observation d9610b3e-a0d7-4463-bf0c-9234d85c5c05 · outbound

This paper cites SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers

Reference 36

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no resolver link, observed 2026-08-07T13:26:42.836200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:42.836200Z digest=sha256:e3fb8f81e19de275176dafcea06d627c9a4f6ae74ac896bd10c4f7b9de9eb18c

Observation 9afae5dc-540b-4f92-a4c2-bded45021d1d · outbound

This paper cites Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 37

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no resolver link, observed 2026-08-07T13:26:42.932095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:42.932095Z digest=sha256:eed40557a7a6c59973aee03c37973cea4e07953839c9ccf570cc62f2a12d6ad7

Observation a346b8cd-a253-4c5c-9b7b-aa2e131af6ce · outbound

This paper cites The State of Sparsity in Deep Neural Networks.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation The State of Sparsity in Deep Neural Networks

Reference 38

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no resolver link, observed 2026-08-07T13:26:43.019228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:43.019228Z digest=sha256:702b334a528b9df8ee1f03cd847884df71517b306ed457dce346ae1d23ed034f

Observation c7a3fb70-8e7b-4539-93cd-b54cf5f4c013 · outbound

This paper cites OTOV2: Automatic, Generic, User-Friendly.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation OTOV2: Automatic, Generic, User-Friendly

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:43.135686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:43.135686Z digest=sha256:e008babc1081a8a978bd1fc48941d0861a4edc1db89b281400bfa788b60a02db

Observation 9ccb7383-9457-4698-a288-9fe3934f6c25 · outbound

This paper cites An accelerated doubly stochastic gradient method with faster explicit model identification.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation An accelerated doubly stochastic gradient method with faster explicit model identification

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:49.121728Z

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=2026-08-07T13:26:43.225426Z digest=sha256:1b060d78593918b82b9247b8dc7ff2c9a71f1876ffa988d2ee293af69e5721fb

Observation 28319253-eaf8-43c9-97ed-65dc204e1023 · outbound

This paper cites Doubly sparse asynchronous learning for stochastic composite optimization.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Doubly sparse asynchronous learning for stochastic composite optimization

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:48.881566Z

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=2026-08-07T13:26:43.353257Z digest=sha256:c4d9551b62b40a3447b76323216ff76d650b4cdff0f4827796078eeba43c74fd

Observation a4c6849c-0ff9-4813-a26f-25ceb34447b2 · outbound

This paper cites Learning to prune deep neural networks via layer-wise optimal brain surgeon, 2017.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Learning to prune deep neural networks via layer-wise optimal brain surgeon, 2017

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:48.663632Z

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=2026-08-07T13:26:43.448064Z digest=sha256:2caa7ea3997d558f2b6125180a46483143ebc1d747706f8d04c295140f73ada5

Observation ebd6d388-d533-4ba5-99fa-7d23d02f8b78 · outbound

This paper cites Lookahead: A far-sighted alternative of magnitude-based pruning, 2020.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Lookahead: A far-sighted alternative of magnitude-based pruning, 2020

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:48.437114Z

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=2026-08-07T13:26:43.564254Z digest=sha256:adbdc5b695d0295c44a0f7b49e52fef5da17ee908b7efb00b29bac3f94c7f2fd

Observation 500cd1d1-7f4d-4835-b3fc-1bf5fdbb296c · outbound

This paper cites Sparsegpt: Massive language models can be accurately pruned in one-shot.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Sparsegpt: Massive language models can be accurately pruned in one-shot

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:43.664006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:43.664006Z digest=sha256:bd3c0202b19b366b9230bb53865e52e1eca684fea893db5ca30217e56be8dd54

Observation 1f917454-8130-4c47-9291-100440aea80f · outbound

This paper cites LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation LoRAPrune: Structured Pruning Meets Low-Rank Parameter-Efficient Fine-Tuning

Reference 45

Resolution
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no resolver link, observed 2026-08-07T13:26:43.815649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:43.815649Z digest=sha256:d4b8201475f12c9f61f2da042d0a417b938fe0b9bbd6326164b150faaae5e6ea

Observation f7c14f6d-cbed-4787-a145-c0831ddd8169 · outbound

This paper cites Slicegpt: Compress large language models by deleting rows and columns.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Slicegpt: Compress large language models by deleting rows and columns

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:48.178101Z

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=2026-08-07T13:26:43.916585Z digest=sha256:838a073d2d14bb9ef6a558ea49fb8cf848c66d020434d25654d2b00914771b04

Observation 3220ec1d-68b9-45d1-923d-ca8146724b72 · outbound

This paper cites Structural pruning for diffusion models.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Structural pruning for diffusion models

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.991011Z

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=2026-08-07T13:26:44.029821Z digest=sha256:1698fbe529a47bea521c905fe1ca3a3fd3c8877c7064a1047357db0b4e4c95bb

Observation f4721ac8-5530-4eb5-a5fa-4488cb4b98f6 · outbound

This paper cites Snapfusion: Text-to-image diffusion model on mobile devices within two seconds.Advances in Neural Information Processing Systems, 36:20662–20678, 2023.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Snapfusion: Text-to-image diffusion model on mobile devices within two seconds.Advances in Neural Information Processing Systems, 36:20662–20678, 2023

Reference 48

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no resolver link, observed 2026-08-07T13:26:44.120121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:44.120121Z digest=sha256:a7e3700074c588c8c2a55748095f5a8cd96cb68c283c5bf056542df68df00adc

Observation 88a0caa5-2ecc-47bf-9450-6f7415e51506 · outbound

This paper cites Diffusion probabilistic model made slim, 2022.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Diffusion probabilistic model made slim, 2022

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.717623Z

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=2026-08-07T13:26:44.237135Z digest=sha256:21370955f9ee375a903a50dd75c4ecb7ad564382b16ef6f6cb1a70a8e96c5425

Observation b5ca6529-7e73-4874-9aa2-068d58790edf · outbound

This paper cites BK-SDM: A Lightweight, Fast, and Cheap Version of Stable Diffusion.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation BK-SDM: A Lightweight, Fast, and Cheap Version of Stable Diffusion

Reference 50

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no resolver link, observed 2026-08-07T13:26:44.338070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:44.338070Z digest=sha256:10c909e469263e9ee0c57969657b488d69e88dc092be370d8ac9666381b097ad

Observation 8415acf1-4361-47ea-9f33-77cdda024bed · outbound

This paper cites Dynamic diffusion transformer.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Dynamic diffusion transformer

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.620967Z

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=2026-08-07T13:26:44.465071Z digest=sha256:5d95a1ac0c76e16048c58f6584b1aad741a3b0688009240f0aa7eef93c8f0e33

Observation 517206ab-ead5-4cc4-8da7-a340dfd44925 · outbound

This paper cites Glam: Efficient scaling of language models with mixture-of-experts.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Glam: Efficient scaling of language models with mixture-of-experts

Reference 52

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no resolver link, observed 2026-08-07T13:26:44.559255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:44.559255Z digest=sha256:9e69d1480a44a22e0ff2558adb80609218b7e0159f246f2e4e6c2396e5f1e943

Observation 729758f1-ea9a-4b58-b05e-5e01bbb395ca · outbound

This paper cites Mixtral of Experts.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Mixtral of Experts

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:44.663680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:44.663680Z digest=sha256:45b209ea972792432459f6cdba76c2d9ca843066ab101e5132490b0a8e0faf5a

Observation 76799ad0-ea43-4e57-9093-ced6f4fb3363 · outbound

This paper cites Self-moe: Towards compositional large language models with self-specialized experts, 2024.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Self-moe: Towards compositional large language models with self-specialized experts, 2024

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.525593Z

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=2026-08-07T13:26:44.752778Z digest=sha256:373906ed35e75bd1b19373ccb23288a6919bbf8c48b242958f4b89ac9f282579

Observation aed279ae-cebe-48d6-8a43-35bc800df1c5 · outbound

This paper cites To- moe: Converting dense large language models to mixture-of-experts through dynamic structural pruning, 2025.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation To- moe: Converting dense large language models to mixture-of-experts through dynamic structural pruning, 2025

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.394849Z

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=2026-08-07T13:26:44.861776Z digest=sha256:fc5e129f5622caeb315c02d0e29c4fffee1a179bfa8c284138650eb760346f9c

Observation 4a4dd355-db97-4f15-858f-7615e824fad8 · outbound

This paper cites Mixture of efficient diffusion experts through automatic interval and sub-network selection.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Mixture of efficient diffusion experts through automatic interval and sub-network selection

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.296721Z

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=2026-08-07T13:26:44.938610Z digest=sha256:2d1a08e5f7943fc0083a01affbfe13c0e9ec0f70ffca7f46dda09aabb4b36af3

Observation ad660535-699d-4f80-9aea-78fb63cbb7d5 · outbound

This paper cites EC-DIT: Scaling diffusion transformers with adaptive expert-choice routing.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation EC-DIT: Scaling diffusion transformers with adaptive expert-choice routing

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.158991Z

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=2026-08-07T13:26:45.053005Z digest=sha256:41b1dbed7ef2d96f785cc0d5445b702cf058b48e51550cdfcb08d11ed83ee6a5

Observation 0319b9d7-4465-492a-a574-e6712320c5c4 · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 58

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no resolver link, observed 2026-08-07T13:26:45.152762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:45.152762Z digest=sha256:d2e34939b585ee8faae54f25b9bfeb29973ca316aa68ec302c5c88663d320cd6

Observation f6b82647-66c4-4f0b-af31-b42270f728c0 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation U-net: Convolutional networks for biomedical image segmentation

Reference 59

Resolution
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no resolver link, observed 2026-08-07T13:26:45.226652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:45.226652Z digest=sha256:86e05e25a6eb0e5dd36c7018f3fa027d334fb783b88e1f3aa8fa9b8028e696a0

Observation 831eb1dd-f98f-4808-b337-483e12691831 · outbound

This paper cites Diffusion models beat gans on image synthesis.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Diffusion models beat gans on image synthesis

Reference 60

Resolution
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no resolver link, observed 2026-08-07T13:26:45.294970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:45.294970Z digest=sha256:c17f1b0f10027802e8e770be3c5a208859d51232fa83c748c9132556d42821c8

Observation 2de5599e-5dd9-4a6b-831e-0343e95912d7 · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Categorical Reparameterization with Gumbel-Softmax

Reference 61

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no resolver link, observed 2026-08-07T13:26:45.414649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:45.414649Z digest=sha256:56a27d3ebc2595b74acafd29ebeca3242c22fefd35a294929feae2e33d7acd8f

Observation f0ee0718-5c71-48eb-b9e0-a8cdf28ce2fa · outbound

This paper cites {GS}hard: Scaling giant models with conditional computation and automatic sharding.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation {GS}hard: Scaling giant models with conditional computation and automatic sharding

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:47.005382Z

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=2026-08-07T13:26:45.492684Z digest=sha256:9c5839e3ba998d146954339153575d0097af8ce7283fb83111aeead7890bce13

Observation bf01e1a3-ed24-46e3-bd31-25450f1027e3 · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.Journal of Machine Learning Research, 23(120):1–39, 2022.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.Journal of Machine Learning Research, 23(120):1–39, 2022

Reference 63

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no resolver link, observed 2026-08-07T13:26:45.543883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:45.543883Z digest=sha256:fe05c5820fc2e5f07e532dc1a027d73c0d311c49d21cc700cb1b2c6ec0e62774

Observation 41a02c16-ae01-42f9-a6a0-0eefeb58f4e9 · outbound

This paper cites Laion- 5b: An open large-scale dataset for training next generation image-text models.Advances in neural information processing systems, 35:25278–25294, 2022.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Laion- 5b: An open large-scale dataset for training next generation image-text models.Advances in neural information processing systems, 35:25278–25294, 2022

Reference 64

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no resolver link, observed 2026-08-07T13:26:45.621457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:45.621457Z digest=sha256:73584d57b1a484f3345a7184616f20b30eb548912b76611d7d530d1f9e01b358

Observation 4667866d-d877-4e45-8f0c-7ec4270e32b1 · outbound

This paper cites Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:26:46.858800Z

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=2026-08-07T13:26:45.712887Z digest=sha256:5cf097e8098639a7dcb889d2d740ca1653126df8a0f682c00ecf3ff9cc0bc90e

Observation 3a71c832-f954-4f73-9b3c-611ab2dbce7a · outbound

This paper cites Microsoft coco: Common objects in context.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Microsoft coco: Common objects in context

Reference 66

Resolution
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no resolver link, observed 2026-08-07T13:26:45.833008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:45.833008Z digest=sha256:8393ea7238c57e07824a296f72031149b960a0af3a9f0852f2a72c1a1eaef652

Observation e0e313c5-1a04-4230-b8a8-339cca75f731 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in neural information processing systems, 30, 2017.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Gans trained by a two time-scale update rule converge to a local nash equilibrium.Advances in neural information processing systems, 30, 2017

Reference 67

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no resolver link, observed 2026-08-07T13:26:45.923763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:45.923763Z digest=sha256:b4106e6f886ed465aad33dd9209b3edaf1340dc3a6e7e908d6c36e559f90f83e

Observation daf4e37e-e9ba-4a2d-8b35-1c2c3fa8e5c4 · outbound

This paper cites Rethinking fid: Towards a better evaluation metric for image generation.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Rethinking fid: Towards a better evaluation metric for image generation

Reference 68

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no resolver link, observed 2026-08-07T13:26:46.015698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:26:46.015698Z digest=sha256:6394758746f11e8da9bdadb85cf8ccf16389b54d6b4bc578240a15b15dedbf64

Observation ac1958bb-4197-4323-9ce1-e552dc9694ef · outbound

This paper cites CLIPScore: A Reference-free Evaluation Metric for Image Captioning.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 69

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no resolver link, observed 2026-08-07T13:26:46.094525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 142fe4fc-64ea-4950-b146-b0a3464d90a8 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 70

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Observation fa5ecffd-ffd1-48c0-b501-12809455cf9e · outbound

This paper cites Decoupled weight decay regularization.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Decoupled weight decay regularization

Reference 71

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Observation 701b981f-4e79-4b58-ac1e-0e2457bfa7c1 · outbound

This paper cites Classifier-Free Diffusion Guidance.

ALTER: All-in-One Layer Pruning and Temporal Expert Routing for Efficient Diffusion Generation Classifier-Free Diffusion Guidance

Reference 72

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Pith citing papers

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