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Paper Citation Record · LEDGER

A Noise is Worth Diffusion Guidance

As of 21 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 17 inbound Pith citation observations for arXiv:2412.03895.

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

pith.paper-citation-record.v1
2412.03895 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:07:59.520339Z

measured 72 of 72 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:15:34.835224Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

55 of 55 outbound references displayed

  • verified exact0
  • verified fuzzy20
  • unresolved35
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 91c9886b-6606-4629-820e-d7f8265b69f6 · outbound

This paper cites Self-Rectifying Diffusion Sampling with Perturbed-Attention Guidance.

A Noise is Worth Diffusion Guidance Self-Rectifying Diffusion Sampling with Perturbed-Attention Guidance

Reference 1

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Observation 257adcc0-8be2-4953-ae8a-43d2a5b6c453 · outbound

This paper cites Attend-and-excite: Attention-based se- mantic guidance for text-to-image diffusion models.

A Noise is Worth Diffusion Guidance Attend-and-excite: Attention-based se- mantic guidance for text-to-image diffusion models

Reference 2

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation a6ed000f-1c38-4bdf-9fae-1735947fda18 · outbound

This paper cites PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.

A Noise is Worth Diffusion Guidance PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 3

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Observation b2eb79b6-8ced-4cc1-b1bc-be5277167430 · outbound

This paper cites CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models.

A Noise is Worth Diffusion Guidance CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models

Reference 4

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source=pdf_text observed=2026-08-11T22:07:59.297379Z digest=sha256:cfb4eace9d5d0b62f1ca2ce9b73c75fe1a7f08a65af756c57a87ffba6146add3

Observation 687ebef7-bc20-4a48-a747-1c0d71e5c6ad · outbound

This paper cites Diffusion models beat gans on image synthesis.

A Noise is Worth Diffusion Guidance Diffusion models beat gans on image synthesis

Reference 5

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Observation 1c276145-5cc3-401b-83e3-bb94e44d66a4 · outbound

This paper cites Scaling recti- fied flow transformers for high-resolution image synthesis.

A Noise is Worth Diffusion Guidance Scaling recti- fied flow transformers for high-resolution image synthesis

Reference 6

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source=pdf_text observed=2026-08-11T22:07:59.306861Z digest=sha256:55e5e4a307d67673c553c11e5bd4df7da3014e89b4a7a4d8e9c3d7fce27aecef

Observation 974f5e74-982f-4a52-a96b-7c8f4e043a47 · outbound

This paper cites ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization.

A Noise is Worth Diffusion Guidance ReNO: Enhancing One-step Text-to-Image Models through Reward-based Noise Optimization

Reference 7

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Observation d351df1f-f7a3-4a9c-9ddc-224f12dced41 · outbound

This paper cites ReNoise: Real Image Inversion Through Iterative Noising.

A Noise is Worth Diffusion Guidance ReNoise: Real Image Inversion Through Iterative Noising

Reference 8

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source=pdf_text observed=2026-08-11T22:07:59.315800Z digest=sha256:a3e526511ae521442da2f16c78cb68fad936c3ad061da9c48df3a59425479cf2

Observation a6422c31-91e7-4867-b27c-ce5e3af6659b · outbound

This paper cites Factorized diffusion: Perceptual illusions by noise decomposition.

A Noise is Worth Diffusion Guidance Factorized diffusion: Perceptual illusions by noise decomposition

Reference 9

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation c13fd3a4-b667-414c-9e26-eea235095968 · outbound

This paper cites Initno: Boosting text-to-image diffu- sion models via initial noise optimization.

A Noise is Worth Diffusion Guidance Initno: Boosting text-to-image diffu- sion models via initial noise optimization

Reference 10

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Observation cc064ca7-ad6c-4fa5-a443-2546a4f1d93d · outbound

This paper cites Deep residual learning for image recognition.

A Noise is Worth Diffusion Guidance Deep residual learning for image recognition

Reference 11

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source=pdf_text observed=2026-08-11T22:07:59.328757Z digest=sha256:fdfc45fc1f10e8e3bc5af7b2280d08b2914b09d6bbf8085e4abfcf20632c1d62

Observation 4b11d6f5-72e3-4bd3-87d3-8b360abaf1d5 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

A Noise is Worth Diffusion Guidance Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 7edb46bf-a10a-4e0e-88da-3d494281f920 · outbound

This paper cites Classifier-Free Diffusion Guidance.

A Noise is Worth Diffusion Guidance Classifier-Free Diffusion Guidance

Reference 13

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source=pdf_text observed=2026-08-11T22:07:59.336832Z digest=sha256:e3f197d31c253f5c39ac54ff66bc7cbf8e5f6183eac2942421fd15b211c6e119

Observation 5f88f05a-bec6-4eb6-b3c6-9e57efd5e137 · outbound

This paper cites Denoising dif- fusion probabilistic models.

A Noise is Worth Diffusion Guidance Denoising dif- fusion probabilistic models

Reference 14

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Observation c3e18637-8f1d-435e-bb75-628f3d8dc754 · outbound

This paper cites Smoothed Energy Guidance: Guiding Diffusion Models with Reduced Energy Curvature of Attention.

A Noise is Worth Diffusion Guidance Smoothed Energy Guidance: Guiding Diffusion Models with Reduced Energy Curvature of Attention

Reference 15

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Observation 93f2521f-0ac7-4118-a4a8-264dfd2cd87b · outbound

This paper cites Improving sample quality of diffusion models us- ing self-attention guidance.

A Noise is Worth Diffusion Guidance Improving sample quality of diffusion models us- ing self-attention guidance

Reference 16

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Observation 2996d7aa-099c-4a9d-a912-4fae15cba1fa · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

A Noise is Worth Diffusion Guidance LoRA: Low-Rank Adaptation of Large Language Models

Reference 17

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Observation b7f5d6d9-f9de-4ba0-9f41-06b65314b7a5 · outbound

This paper cites How can we know what language models know? Trans- actions of the Association for Computational Linguistics , 8: 423–438, 2020.

A Noise is Worth Diffusion Guidance How can we know what language models know? Trans- actions of the Association for Computational Linguistics , 8: 423–438, 2020

Reference 18

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 4d991ad8-7e5e-4d2b-9f62-a4de848bd4ff · outbound

This paper cites Distilling diffusion models into condi- 9 tional gans.

A Noise is Worth Diffusion Guidance Distilling diffusion models into condi- 9 tional gans

Reference 19

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 77f8dcea-63b0-4d67-b806-0a57f632f232 · outbound

This paper cites Elucidating the design space of diffusion-based generative models.

A Noise is Worth Diffusion Guidance Elucidating the design space of diffusion-based generative models

Reference 20

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation a4e6ae2a-ee10-4096-b904-472b74864a39 · outbound

This paper cites Guiding a Diffusion Model with a Bad Version of Itself.

A Noise is Worth Diffusion Guidance Guiding a Diffusion Model with a Bad Version of Itself

Reference 21

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Observation d392da98-83b3-44c9-ba36-3b828cbaa62f · outbound

This paper cites Model-Agnostic Human Preference Inversion in Diffusion Models.

A Noise is Worth Diffusion Guidance Model-Agnostic Human Preference Inversion in Diffusion Models

Reference 22

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Observation 035e9b97-ad4f-4a99-89c1-a373cb04499c · outbound

This paper cites Pick-a-pic: An open dataset of user preferences for text-to-image generation.

A Noise is Worth Diffusion Guidance Pick-a-pic: An open dataset of user preferences for text-to-image generation

Reference 23

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Observation 33a03b9a-1544-48fb-9d7f-3307cb24aff3 · outbound

This paper cites SDXL-Lightning: Progressive Adversarial Diffusion Distillation.

A Noise is Worth Diffusion Guidance SDXL-Lightning: Progressive Adversarial Diffusion Distillation

Reference 24

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Observation cd9721de-3858-4eaf-b5f2-e161ee3d5cc5 · outbound

This paper cites Microsoft coco: Common objects in context.

A Noise is Worth Diffusion Guidance Microsoft coco: Common objects in context

Reference 25

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Observation 0733c6db-4fff-496c-a08c-95af9f82a3a8 · outbound

This paper cites DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models.

A Noise is Worth Diffusion Guidance DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models

Reference 26

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source=pdf_text observed=2026-08-11T22:07:59.391054Z digest=sha256:20934c0829d9a86a0857ac80186fcd8463f2335ef6c23a5b8766cd15e1d8d96d

Observation b15e95b1-9322-4bcb-a2d1-73d0e053a80f · outbound

This paper cites Guided image synthesis via initial image editing in diffusion model.

A Noise is Worth Diffusion Guidance Guided image synthesis via initial image editing in diffusion model

Reference 27

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation c8a1b9ab-5b7f-46e7-9a72-314579af155a · outbound

This paper cites The Lottery Ticket Hypothesis in Denoising: Towards Semantic-Driven Initialization.

A Noise is Worth Diffusion Guidance The Lottery Ticket Hypothesis in Denoising: Towards Semantic-Driven Initialization

Reference 28

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Observation 63e61bb4-40c0-4173-a64c-6ec1d23759d7 · outbound

This paper cites Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models.

A Noise is Worth Diffusion Guidance Lightning-Fast Image Inversion and Editing for Text-to-Image Diffusion Models

Reference 29

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source=pdf_text observed=2026-08-11T22:07:59.403936Z digest=sha256:13b41f16fd3a6acfc2bcb1c053d19e629f66213d8fd51e3ee2a305fe1a3ff325

Observation 7b2c9165-610e-4944-aef1-b8a3374a7602 · outbound

This paper cites On distillation of guided diffusion models.

A Noise is Worth Diffusion Guidance On distillation of guided diffusion models

Reference 30

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Observation 5c3ac832-6dfc-470b-8551-86c4e316fdae · outbound

This paper cites Effective real image editing with accelerated iter- ative diffusion inversion.

A Noise is Worth Diffusion Guidance Effective real image editing with accelerated iter- ative diffusion inversion

Reference 31

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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Observation 5ea6688a-5e64-4a16-9b38-8cdfa8fa7bdb · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

A Noise is Worth Diffusion Guidance SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 32

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source=pdf_text observed=2026-08-11T22:07:59.416031Z digest=sha256:378e84744ce1d26d048661bc92c46a19d8c75daa827ad13ba928242147a9a73c

Observation 88252290-bb18-4e24-893c-7fda80f56718 · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

A Noise is Worth Diffusion Guidance DreamFusion: Text-to-3D using 2D Diffusion

Reference 33

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Observation 19592256-3ec2-42bf-8468-88060e71844c · outbound

This paper cites Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization.

A Noise is Worth Diffusion Guidance Not All Noises Are Created Equally:Diffusion Noise Selection and Optimization

Reference 34

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Observation be7c6905-81f3-4838-9a07-a47a22598ef9 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

A Noise is Worth Diffusion Guidance Learning transferable visual models from natural language supervi- sion

Reference 35

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raw_fallback, observed 2026-08-11T22:07:59.976081Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T22:07:59.430040Z digest=sha256:5a1cd8b56ab3682ad69d5ccf740935dd937a2d92ffd0ba078a9aa2d54b9d46b2

Observation 17c7aac3-1eeb-4927-b006-fd4c108b87c5 · outbound

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

A Noise is Worth Diffusion Guidance High-resolution image synthesis with latent diffusion models

Reference 36

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raw_fallback, observed 2026-08-11T22:07:59.963727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T22:07:59.435061Z digest=sha256:3deeb77682c76c73d147e8e3639e491652310e53d0a8ac619d4c2fbbc7c515c4

Observation cf193424-1928-41d8-b9e5-fd2daa6c476d · outbound

This paper cites CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling.

A Noise is Worth Diffusion Guidance CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:07:59.439788Z digest=sha256:f043ce39257656c23cda8937a9218e2ddf7fe23d1a59a961c968585da3e8d497

Observation b6cc70db-2575-441c-bd71-0e2e252b7750 · outbound

This paper cites No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models.

A Noise is Worth Diffusion Guidance No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models

Reference 38

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no resolver link, observed 2026-08-11T22:07:59.444646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:07:59.444646Z digest=sha256:70247183718b3765af83fbb42777dc6631c328714faf5fa871a0f59c995555bc

Observation bc4469e1-7af1-45bf-ad56-5cf6f34cac3b · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

A Noise is Worth Diffusion Guidance Photorealistic text-to-image diffusion models with deep language understanding

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-11T22:07:59.950308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T22:07:59.449822Z digest=sha256:1cdd004d1bdc15f1331c2466daf00a1fb08fae8ebdca6177f8900d9a2f372c7f

Observation c51980de-3341-4063-b578-7b740918c999 · outbound

This paper cites Improved techniques for training gans.

A Noise is Worth Diffusion Guidance Improved techniques for training gans

Reference 40

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no resolver link, observed 2026-08-11T22:07:59.454930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:07:59.454930Z digest=sha256:153039015d5b2894f3fc3c33728bf0932f0acd56f504566d15601b91e666d443

Observation 13804481-248b-4deb-ab82-2f1c0c2bfc71 · outbound

This paper cites Generating images of rare concepts using pre- trained diffusion models.

A Noise is Worth Diffusion Guidance Generating images of rare concepts using pre- trained diffusion models

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:07:59.929754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T22:07:59.459243Z digest=sha256:de839ed9abcbec4fd6b22bca3c4d75f81c0553d99b12825c8f1b6aa4067284e6

Observation 6a15aaf1-2a32-4d4e-86f4-11e9fa450977 · outbound

This paper cites Adversarial diffusion distillation.

A Noise is Worth Diffusion Guidance Adversarial diffusion distillation

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-11T22:07:59.462980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:07:59.462980Z digest=sha256:02bcb5cca4396881736a63890334b7a3394aa155e9ab1a26946dd90d6f022874

Observation 339fdf9b-8869-4406-9f59-136907495d60 · outbound

This paper cites Improved aesthetic predictor.

A Noise is Worth Diffusion Guidance Improved aesthetic predictor

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:07:59.908074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T22:07:59.468008Z digest=sha256:69cc75833928fe0864e26c52e43e5b293b9e2ea699ea2ccbc2e30e3d5cb39bbb

Observation 100d95e4-2ef8-427e-9ec4-ed09e9a35ff7 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

A Noise is Worth Diffusion Guidance Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:07:59.894402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T22:07:59.472084Z digest=sha256:e8942e74fc18f38601f0cf496d8efa5e3f7e5318cfe9028eebb27db28c9b29da

Observation 63d537de-bad1-404b-9709-445113daaf3f · outbound

This paper cites AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts.

A Noise is Worth Diffusion Guidance AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-11T22:07:59.476374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:07:59.476374Z digest=sha256:0190974e7c8b1fd184cc3c9bb98f9654dba195f5f31e4573f4680a57bf7cc50d

Observation 5f63793a-2847-4987-9d55-27e553caa6e1 · outbound

This paper cites Denoising Diffusion Implicit Models.

A Noise is Worth Diffusion Guidance Denoising Diffusion Implicit Models

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T22:07:59.480885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:07:59.480885Z digest=sha256:a4c2db6e7d36bf8115d825f44e015268dfb7b27678f7d7dfec2a1cb680ca24cd

Observation 408f885a-cb1b-4bf1-b7d5-d4fb1ab0d7fe · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

A Noise is Worth Diffusion Guidance Score-Based Generative Modeling through Stochastic Differential Equations

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-11T22:07:59.484935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:07:59.484935Z digest=sha256:8daaedceddca0016bd7e78fef06f129cba3d79517966d7db7b88d4fac8cf2e08

Observation 0083e726-aedd-41bf-a299-acac137cae72 · outbound

This paper cites Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis.

A Noise is Worth Diffusion Guidance Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-11T22:07:59.489020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:07:59.489020Z digest=sha256:cb646cbebb9e08d569a82033bb2a5f9934960a1674c388fc98d10b9edbb8c8e3

Observation 3e87c187-d8d4-434f-847c-542166fbb186 · outbound

This paper cites Imagere- ward: Learning and evaluating human preferences for text- to-image generation.(2023).

A Noise is Worth Diffusion Guidance Imagere- ward: Learning and evaluating human preferences for text- to-image generation.(2023)

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:07:59.880068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T22:07:59.493886Z digest=sha256:6109f23f6b212722148e7e43bc39a5997def61a3f48f7da631bff8ee4cf642d0

Observation 4ecc98a0-35ee-4d31-ac87-e3933db5b00a · outbound

This paper cites Good Seed Makes a Good Crop: Discovering Secret Seeds in Text-to-Image Diffusion Models.

A Noise is Worth Diffusion Guidance Good Seed Makes a Good Crop: Discovering Secret Seeds in Text-to-Image Diffusion Models

Reference 50

Resolution
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no resolver link, observed 2026-08-11T22:07:59.497845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:07:59.497845Z digest=sha256:cfb370447627a06cec60a2fddae5150e96fa0b3b17ee13f12c73e7337ada63c6

Observation a3ad7ce2-b0f2-48ef-ade4-b3c65c4555cc · outbound

This paper cites Conditional prompt learning for vision-language mod- els.

A Noise is Worth Diffusion Guidance Conditional prompt learning for vision-language mod- els

Reference 51

Resolution
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no resolver link, observed 2026-08-11T22:07:59.502738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:07:59.502738Z digest=sha256:9f6790caf0daacb11896b2f2aa63bcc3c7b295e1bc02acaaea90ecf9ab6bf0b0

Observation 977be98f-cecb-41cf-ab2c-b3052241437c · outbound

This paper cites Learning to prompt for vision-language models.

A Noise is Worth Diffusion Guidance Learning to prompt for vision-language models

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-11T22:07:59.507369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:07:59.507369Z digest=sha256:c4a31d312765cb835a44ea2a95810a4181a04014a352a39b65ad9737b8eb25c9

Observation b1b623a8-5a10-4382-b087-7546ff81eadb · outbound

This paper cites an unresolved cited work.

A Noise is Worth Diffusion Guidance Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-11T22:07:59.835007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T22:07:59.516125Z digest=sha256:b35ad7a4f16206200171b5b37ce02d4a843f625d065a09d6de4066c3097e9564

Observation 37e917ed-f122-4777-a840-7fce9691639b · outbound

This paper cites Twocarsonthestreet.

A Noise is Worth Diffusion Guidance Twocarsonthestreet

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:07:59.820590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T22:07:59.520339Z digest=sha256:2c9798ae7e7fdc2bdb41d6e6d0100e4bc2b5ff86acb9a31e7c9f766beae4bd60

Observation ad312255-9e8b-4d62-b2e6-16606a37ef4f · outbound

This paper cites an unresolved cited work.

A Noise is Worth Diffusion Guidance Unresolved cited work

Reference 2022

Resolution
unresolved
raw_fallback, observed 2026-08-11T22:07:59.847516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-11T22:07:59.511282Z digest=sha256:73eb868497953038465737aebc5bd1d7e590261f91220276c834eb9b1710381f

Pith citing papers

Observation c7ad21ae-2427-481e-a4cd-c8abcbb6ec26 · inbound

Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps cites this paper.

Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps A Noise is Worth Diffusion Guidance

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-20T11:45:17.612903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-20T11:45:17.473970Z digest=sha256:6cc2faa7ae97f2b23a71e97bb25d352007971b3cdd8241c2788d15c86f515e0b

Observation 7a44a024-240b-4b94-ac15-704118652c01 · inbound

REG: Rectified Gradient Guidance for Conditional Diffusion Models cites this paper.

REG: Rectified Gradient Guidance for Conditional Diffusion Models A Noise is Worth Diffusion Guidance

Reference 1

Resolution
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no resolver link, observed 2026-08-09T22:20:18.181192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T22:20:18.181192Z digest=sha256:ba6ead8f7e78622e5ea4d0c4aefba290ea8e886e48499ebb04acc54ee8b6c7e0

Observation 8c7dfb10-a8f8-4c67-ab17-a151acaa46f5 · inbound

From Reflection to Perfection: Scaling Inference-Time Optimization for Text-to-Image Diffusion Models via Reflection Tuning cites this paper.

From Reflection to Perfection: Scaling Inference-Time Optimization for Text-to-Image Diffusion Models via Reflection Tuning A Noise is Worth Diffusion Guidance

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-16T11:15:34.835224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:15:34.835224Z digest=sha256:11b4697f334da8a86298d1869a9c30b32ae62f6b1c9fd37a93d58565ee116ae3

Observation 7847d3a9-e927-45de-a57d-1f04bb30df03 · inbound

Towards Self-Improvement of Diffusion Models via Group Preference Optimization cites this paper.

Towards Self-Improvement of Diffusion Models via Group Preference Optimization A Noise is Worth Diffusion Guidance

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T21:03:29.108005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:03:29.108005Z digest=sha256:0824c8c415415cba66cbfd7267f176f6cc5d2655182dcd1fd1eb336a194dbd6b

Observation 9e3dc6de-d48a-437a-b425-c50d56a88899 · inbound

Scaling Image and Video Generation via Test-Time Evolutionary Search cites this paper.

Scaling Image and Video Generation via Test-Time Evolutionary Search A Noise is Worth Diffusion Guidance

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T14:49:40.497049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:49:40.497049Z digest=sha256:ad1bc24bf63bb18ef80531429705024bfc2cb5b52fd295b7f0b5dabda0f48288

Observation a63970fd-0051-4957-a9a0-b5b1fbf482ec · inbound

Test-Time Scaling of Diffusion Models via Noise Trajectory Search cites this paper.

Test-Time Scaling of Diffusion Models via Noise Trajectory Search A Noise is Worth Diffusion Guidance

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T14:28:44.141169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:28:44.141169Z digest=sha256:bfcad0f051d76f4b1a43c05ce215ae282c03c248babbfd2ab7665a91446fd721

Observation cd27d005-fc84-4ac4-a371-a803a807248b · inbound

Steering Your Diffusion Policy with Latent Space Reinforcement Learning cites this paper.

Steering Your Diffusion Policy with Latent Space Reinforcement Learning A Noise is Worth Diffusion Guidance

Reference 69

Resolution
verified exact
arxiv_id, observed 2026-05-17T21:55:46.268218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-17T21:55:46.183007Z digest=sha256:1cd03713e6b408302a4fbc8c39a49bd1880110306680d72c9b9528811dcd0aa6

Observation a34d4aac-7f57-4650-ace5-9716684ff403 · inbound

FastInit: Fast Noise Initialization for Temporally Consistent Video Generation cites this paper.

FastInit: Fast Noise Initialization for Temporally Consistent Video Generation A Noise is Worth Diffusion Guidance

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T23:49:53.244659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:49:53.244659Z digest=sha256:4d775e6a0c96ce5c020a0a17c7f7633721309850a04558b995a881559515f66e

Observation fe783b7e-64de-4339-89d2-0d25d89b11a1 · inbound

Brownian Bridge Diffusion for Sequential Recommendation cites this paper.

Brownian Bridge Diffusion for Sequential Recommendation A Noise is Worth Diffusion Guidance

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-19T05:57:08.342737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-19T05:53:22.577986Z digest=sha256:ae6abe03d5d52a289dafe50a4f488eb712b86b8270681dffaa3576ab3c554c75

Observation 3283602b-01b2-4946-8fba-703978041443 · inbound

It's Never Too Late: Noise Optimization for Collapse Recovery in Trained Diffusion Models cites this paper.

It's Never Too Late: Noise Optimization for Collapse Recovery in Trained Diffusion Models A Noise is Worth Diffusion Guidance

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-16T17:53:11.679914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T17:51:32.439732Z digest=sha256:06b2ec4f922f9c94119bbad5c24d026cc7b6677337e6158307f29c03743aaa35

Observation c0b3f1bc-e01f-4310-bb9a-ed1b92ff9e09 · inbound

Action-to-Action Flow Matching cites this paper.

Action-to-Action Flow Matching A Noise is Worth Diffusion Guidance

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-16T06:57:29.209240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T06:53:35.153155Z digest=sha256:44740703a54e86dc5b68478a3d77b52d3835cb073e5bf8c895482d05d4106680

Observation 3ffcaba3-6c60-4803-9bee-942257c3cb28 · inbound

FASTER: Value-Guided Sampling for Fast RL cites this paper.

FASTER: Value-Guided Sampling for Fast RL A Noise is Worth Diffusion Guidance

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-10T02:48:26.496057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T02:47:36.475845Z digest=sha256:d3095844fa36246076392225899b5aa0533e2cba134a46f10130a9ba102f49c8

Observation de7f9d40-1ed9-49bf-a3e8-fe3219b433e4 · inbound

Oracle Noise: Faster Semantic Spherical Alignment for Interpretable Latent Optimization cites this paper.

Oracle Noise: Faster Semantic Spherical Alignment for Interpretable Latent Optimization A Noise is Worth Diffusion Guidance

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:06:12.628243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-08T06:58:09.085573Z digest=sha256:a2e17d95b93d420d2b96d92cc4f866f1bbec4aaef846078d20c67231a0fa23f8

Observation c3345735-a245-4088-ae88-ba31639e26a6 · inbound

NoiseRater: Meta-Learned Noise Valuation for Diffusion Model Training cites this paper.

NoiseRater: Meta-Learned Noise Valuation for Diffusion Model Training A Noise is Worth Diffusion Guidance

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-12T01:46:13.895476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-12T01:44:04.922621Z digest=sha256:074a0b16f7e1c6f44dbbbf336fcff1123df4429947770f42753530e4d4d893a7

Observation 46bfb084-7d00-44a3-9ea8-c036a9735682 · inbound

Colored Noise Diffusion Sampling cites this paper.

Colored Noise Diffusion Sampling A Noise is Worth Diffusion Guidance

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-06-29T07:53:13.723949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-29T07:47:44.501736Z digest=sha256:dfaec47cd2caae5d68ff47cf296c3480550f97c18ed6485153765c822d9c6280

Observation e0dec77f-a1fb-431a-a882-1ee21d626a09 · inbound

Parallel Tempering Initial Sampling in Inference-Time Reward Alignment cites this paper.

Parallel Tempering Initial Sampling in Inference-Time Reward Alignment A Noise is Worth Diffusion Guidance

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-06-28T23:32:47.427108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-28T23:28:22.532621Z digest=sha256:261f9cb39d53d8e6ea5f051357dbb40a6279858aa24b06e99e9cae2f112218bc

Observation e2bfb4e8-d8ef-4a17-bb12-c9f71ac95335 · inbound

Where Should Action Generation Begin? A Learnable Source Prior for Generative Robot Policies cites this paper.

Where Should Action Generation Begin? A Learnable Source Prior for Generative Robot Policies A Noise is Worth Diffusion Guidance

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-07-03T20:18:57.406686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T01:24:08.136911Z digest=sha256:e8ec8ae94479d8a8d04ca5686c95b81db1f264af03f545c0d106ab929eb5a965