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Paper Citation Record · LEDGER

On the Importance of Noise Scheduling for Diffusion Models

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 45 inbound Pith citation observations for arXiv:2301.10972.

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

pith.paper-citation-record.v1
2301.10972 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 45 of 45 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:53:47.826204Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-07T18:04:00.522746Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation feb62fa8-d326-46ce-aa4b-65560d38d27b · inbound

Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model cites this paper.

Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model On the Importance of Noise Scheduling for Diffusion Models

Reference 2

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arxiv_id, observed 2026-05-16T22:06:48.418450Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-16T22:06:48.384329Z digest=sha256:379e13c350b5795f8f3d69df9f175a68ea25697894c66a179d119d91d21eb7f5

Observation 0b97c23e-7c0e-41a4-b338-d17763dd4934 · inbound

Stealing Training Graphs from Graph Neural Networks cites this paper.

Stealing Training Graphs from Graph Neural Networks On the Importance of Noise Scheduling for Diffusion Models

Reference 3

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source=pdf_text observed=2026-08-12T18:53:47.826204Z digest=sha256:f076582962b78c98d68416d73830735850b914e25979847d2a126a104563f059

Observation 98d40e71-dce7-478d-b8e4-bd683fd65328 · inbound

DiffSLT: Enhancing Diversity in Sign Language Translation via Diffusion Model cites this paper.

DiffSLT: Enhancing Diversity in Sign Language Translation via Diffusion Model On the Importance of Noise Scheduling for Diffusion Models

Reference 6

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source=pdf_text observed=2026-08-12T12:24:55.216805Z digest=sha256:b02e5cce46bf41d30b058ddc52a95e09d892dd72ff3423141c71c0ec926cd4cd

Observation b207eb70-84dd-4afc-ad05-6dcb9916dc1a · inbound

Mixed-State Quantum Denoising Diffusion Probabilistic Model cites this paper.

Mixed-State Quantum Denoising Diffusion Probabilistic Model On the Importance of Noise Scheduling for Diffusion Models

Reference 44

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source=pdf_text observed=2026-08-12T12:01:32.600061Z digest=sha256:aee427434b89f35e0694b8053148cb8e0fb69208b958c856e1dfd6c4d800be4c

Observation e5a387af-de49-4c5b-b64f-a7e83a5002dd · inbound

A solvable generative model with a linear, one-step denoiser cites this paper.

A solvable generative model with a linear, one-step denoiser On the Importance of Noise Scheduling for Diffusion Models

Reference 7

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source=pdf_text observed=2026-08-12T12:01:21.784199Z digest=sha256:6f50c710d5dcb14a4e20f85c3ec3bf88649a3260c7d9f02018e7df1044319bc5

Observation 61e65d59-bd28-4fef-adbf-a883bfe35f51 · inbound

Enhancing Sample Generation of Diffusion Models using Noise Level Correction cites this paper.

Enhancing Sample Generation of Diffusion Models using Noise Level Correction On the Importance of Noise Scheduling for Diffusion Models

Reference 2024

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source=pdf_text observed=2026-08-11T20:45:34.400652Z digest=sha256:c4755fab25a9d72295cf7285b51aeba8c9e71b15582f9a12327428421b8373bc

Observation bcb4c548-b814-4495-9986-9de1d2aa349f · inbound

3D-Consistent Image Inpainting with Diffusion Models cites this paper.

3D-Consistent Image Inpainting with Diffusion Models On the Importance of Noise Scheduling for Diffusion Models

Reference 4

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source=pdf_text observed=2026-08-11T20:18:43.305461Z digest=sha256:abe9d785a8bdeb2b6ee06c06fc554c7f516a284695ea82556976e2ec457c0b15

Observation b16fbc1c-6d38-4af9-a44e-840693e39ef1 · inbound

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation cites this paper.

Diffusion-based Data Augmentation and Knowledge Distillation with Generated Soft Labels Solving Data Scarcity Problems of SAR Oil Spill Segmentation On the Importance of Noise Scheduling for Diffusion Models

Reference 10

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source=pdf_text observed=2026-08-11T18:18:12.862918Z digest=sha256:12c6d231dc0ef2b340a410e09b7ac098bb5eb84aa846b9d5e794ea8f2aa0302d

Observation 99d99a69-1633-4d4c-a131-8c0a580e4a7d · inbound

AsyncDSB: Schedule-Asynchronous Diffusion Schr\"odinger Bridge for Image Inpainting cites this paper.

AsyncDSB: Schedule-Asynchronous Diffusion Schr\"odinger Bridge for Image Inpainting On the Importance of Noise Scheduling for Diffusion Models

Reference 8

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source=arxiv_source observed=2026-08-11T18:14:34.982579Z digest=sha256:67975fc6829752906b1c6aca093a0bb6ce76f51ec3d92a61fbf7ecea87955552

Observation 2b9eb0c4-07be-4626-9a91-4e3e7d96b49b · inbound

MSC: Multi-Scale Spatio-Temporal Causal Attention for Autoregressive Video Diffusion cites this paper.

MSC: Multi-Scale Spatio-Temporal Causal Attention for Autoregressive Video Diffusion On the Importance of Noise Scheduling for Diffusion Models

Reference 5

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source=pdf_text observed=2026-08-11T16:45:12.671330Z digest=sha256:aff4bdf01e36a909d78e15a5f72701b0f27d393d4604d56c8a60f29148fa1d02

Observation b5a0119d-6323-4acc-af23-6ab7f5203d03 · inbound

MOVIS: Enhancing Multi-Object Novel View Synthesis for Indoor Scenes cites this paper.

MOVIS: Enhancing Multi-Object Novel View Synthesis for Indoor Scenes On the Importance of Noise Scheduling for Diffusion Models

Reference 4

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source=pdf_text observed=2026-08-11T14:58:48.341462Z digest=sha256:f86f419716b7d55df7d6c33354253f4371ae58bae9eed388ebfa6d3710a2ec59

Observation d23cdeee-dccc-42e5-91c7-345a749c17a9 · inbound

Efficient Scaling of Diffusion Transformers for Text-to-Image Generation cites this paper.

Efficient Scaling of Diffusion Transformers for Text-to-Image Generation On the Importance of Noise Scheduling for Diffusion Models

Reference 2024

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no resolver link, observed 2026-08-11T14:11:00.529321Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:11:00.529321Z digest=sha256:b808ad180f6db068488d00b6d5da0010fd0444bf1a29c9ca7592d5cd09d891b4

Observation 3526aca8-b0f8-4071-ba9b-ba90ade445ff · inbound

Semantics-Guided Diffusion for Deep Joint Source-Channel Coding in Wireless Image Transmission cites this paper.

Semantics-Guided Diffusion for Deep Joint Source-Channel Coding in Wireless Image Transmission On the Importance of Noise Scheduling for Diffusion Models

Reference 40

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no resolver link, observed 2026-08-10T22:41:50.476658Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:41:50.476658Z digest=sha256:5bd128c9318019ad4c558a429096f424ef42ef9b9b70a73bda37ec8a8cbd28ee

Observation 610c0e48-b34e-48b6-be5f-9aab5e2955e9 · inbound

Cosmos World Foundation Model Platform for Physical AI cites this paper.

Cosmos World Foundation Model Platform for Physical AI On the Importance of Noise Scheduling for Diffusion Models

Reference 24

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arxiv_id, observed 2026-05-10T23:38:45.368038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-10T23:38:44.933410Z digest=sha256:899d8ad96afd73a27779aea4eaad52ad33015ff98ebe3cc43cc476c8dfc2b0ca

Observation 1d079127-74fa-4f5a-986d-a175d64d090a · inbound

SPAR3D: Stable Point-Aware Reconstruction of 3D Objects from Single Images cites this paper.

SPAR3D: Stable Point-Aware Reconstruction of 3D Objects from Single Images On the Importance of Noise Scheduling for Diffusion Models

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:31:40.903222Z digest=sha256:3d0dcd8f1c15416164a26b311802b1cfdec6231113d1664b0c2db3572708d6b3

Observation 145044e5-8078-4acb-9d1a-bc66fc1393b8 · inbound

Generative diffusion model with inverse renormalization group flows cites this paper.

Generative diffusion model with inverse renormalization group flows On the Importance of Noise Scheduling for Diffusion Models

Reference 37

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source=arxiv_source observed=2026-08-10T20:18:46.774132Z digest=sha256:ce8de2cfde3676c23fe5d5d93483c0102108f79fe4de5f27e7402edfb898d3a3

Observation e859a5d1-ce54-47da-96af-7ad55d02d452 · inbound

High-Order Matching for One-Step Shortcut Diffusion Models cites this paper.

High-Order Matching for One-Step Shortcut Diffusion Models On the Importance of Noise Scheduling for Diffusion Models

Reference 1994

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no resolver link, observed 2026-08-09T18:10:52.961488Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-09T18:10:52.961488Z digest=sha256:73813ee105332a1a0db022b657f7a6beb25dfa357c9056f17bde8ca08a1cc2d5

Observation 5eed17d4-cfec-42fc-9d1b-738cad74d319 · inbound

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion cites this paper.

ShapeShifter: 3D Variations Using Multiscale and Sparse Point-Voxel Diffusion On the Importance of Noise Scheduling for Diffusion Models

Reference 13

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no resolver link, observed 2026-08-09T13:04:50.546772Z

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source=pdf_text observed=2026-08-09T13:04:50.546772Z digest=sha256:204ea7c7631f375b62a2ed5626b3a6cde55e5f567627caf304b37d47d5084f25

Observation 6f960809-978e-4af1-8aa3-233748898f98 · inbound

A Comprehensive Review on Noise Control of Diffusion Model cites this paper.

A Comprehensive Review on Noise Control of Diffusion Model On the Importance of Noise Scheduling for Diffusion Models

Reference 18

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no resolver link, observed 2026-08-08T21:59:05.485246Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T21:59:05.485246Z digest=sha256:65b8b2257df9d190d88a2165091512aab1affaf926d35589fb43137cd6f7cb02

Observation 1ef039a6-a8aa-4e76-9955-926481e5f4a8 · inbound

History-Guided Video Diffusion cites this paper.

History-Guided Video Diffusion On the Importance of Noise Scheduling for Diffusion Models

Reference 9

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arxiv_id, observed 2026-05-16T12:00:14.712244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-16T12:00:14.672729Z digest=sha256:9d6ff7e9e0cd28c2f810011636a0c942d6e19fdb1adf074aeba3d6c4408f8f7b

Observation 06277f73-2f67-452b-ab90-b4ee42161db0 · inbound

Pippo: High-Resolution Multi-View Humans from a Single Image cites this paper.

Pippo: High-Resolution Multi-View Humans from a Single Image On the Importance of Noise Scheduling for Diffusion Models

Reference 10

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-08T11:39:18.220531Z digest=sha256:82b01f37cf383af227ddcded9c8bcc69f202b801ca30bcc49ffcc4eabb098d28

Observation ac36a447-91c1-4df3-94c7-b3435017f1ed · inbound

Disentangling Total-Variance and Signal-to-Noise-Ratio Improves Diffusion Models cites this paper.

Disentangling Total-Variance and Signal-to-Noise-Ratio Improves Diffusion Models On the Importance of Noise Scheduling for Diffusion Models

Reference 36

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source=arxiv_source observed=2026-08-08T04:39:22.092846Z digest=sha256:b354925270fbe524efc62df1c7fae42c92fe8dc668fff8f6c92af60470723226

Observation d2d1cd3e-5ee0-40f6-a82c-8fd89034f1e4 · inbound

A First-order Generative Bilevel Optimization Framework for Diffusion Models cites this paper.

A First-order Generative Bilevel Optimization Framework for Diffusion Models On the Importance of Noise Scheduling for Diffusion Models

Reference 6

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no resolver link, observed 2026-08-07T23:43:37.735189Z

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source=arxiv_source observed=2026-08-07T23:43:37.735189Z digest=sha256:35ad36f4bc7ebf1c21663be190e5d410197955a0e9998e6f49e1943831649228

Observation d5c1f7a4-beb0-4e03-bb6d-48374e018781 · inbound

Beyond the Frame: Generating 360 Panoramic Videos from Perspective Videos cites this paper.

Beyond the Frame: Generating 360 Panoramic Videos from Perspective Videos On the Importance of Noise Scheduling for Diffusion Models

Reference 10

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arxiv_id, observed 2026-05-22T19:55:05.070573Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-22T19:54:28.310854Z digest=sha256:e074f03e92ac44e3eaeae59f0ae638f6e14db39fcf0cf96becb4171d8baf627f

Observation e2567bcb-3038-43f7-8e03-fd6bc408c68f · inbound

DiffER: Categorical Diffusion for Chemical Retrosynthesis cites this paper.

DiffER: Categorical Diffusion for Chemical Retrosynthesis On the Importance of Noise Scheduling for Diffusion Models

Reference 15

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source=pdf_text observed=2026-08-07T12:44:09.147850Z digest=sha256:4589236e990e78869962dad1f2f3900ef298cd6aef6369999d4d9d4441aa5c48

Observation 0d37f516-4750-4ca1-9301-967f6e209491 · inbound

NoiseAR: AutoRegressing Initial Noise Prior for Diffusion Models cites this paper.

NoiseAR: AutoRegressing Initial Noise Prior for Diffusion Models On the Importance of Noise Scheduling for Diffusion Models

Reference 6

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source=pdf_text observed=2026-08-07T11:51:32.141743Z digest=sha256:3e955740d673290e2fdef844870a71c2fdcb4d1310c5356ef34bc56ff6d28911

Observation 8b01cd1a-fce1-42ac-a399-db9778cbb11e · inbound

Beyond Blur: A Fluid Perspective on Generative Diffusion Models cites this paper.

Beyond Blur: A Fluid Perspective on Generative Diffusion Models On the Importance of Noise Scheduling for Diffusion Models

Reference 5

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arxiv_id, observed 2026-05-19T08:17:10.940605Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-19T08:14:42.654017Z digest=sha256:0375fd8e6aba6723b46f80681130646aee254d35ad56b4ecb659c9b3cb1f610e

Observation 375943c6-be97-4d0c-b731-3986784ea319 · inbound

Incorporating Pre-trained Diffusion Models in Solving the Schr\"odinger Bridge Problem cites this paper.

Incorporating Pre-trained Diffusion Models in Solving the Schr\"odinger Bridge Problem On the Importance of Noise Scheduling for Diffusion Models

Reference 5

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source=pdf_text observed=2026-08-05T16:41:03.341134Z digest=sha256:a1ded3d2d5cbb29679a16e3c384e2bf5ff145dc64f9fe25b348ae71abb756daa

Observation 9666a306-50c1-4b0d-9813-7fe14ffe877b · inbound

NoiseShift: Resolution-Aware Noise Recalibration for Better Low-Resolution Image Generation cites this paper.

NoiseShift: Resolution-Aware Noise Recalibration for Better Low-Resolution Image Generation On the Importance of Noise Scheduling for Diffusion Models

Reference 4

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arxiv_id, observed 2026-05-21T21:44:22.954581Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-21T21:41:29.502472Z digest=sha256:4c148958a59fddb3f16149fdd1b0b5293bf8cf12bae4959f2b2601378499e48e

Observation 71222710-f588-4aef-a23d-073e33cec4cc · inbound

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization cites this paper.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization On the Importance of Noise Scheduling for Diffusion Models

Reference 4

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source=pdf_text observed=2026-08-04T11:25:33.852695Z digest=sha256:6bfc5020111925e670aba3e59360700139866c8cb1d33fec2f0fb1ca8d723eae

Observation b2e3c0e0-06c0-4587-9278-38e3d2fc6054 · inbound

World Simulation with Video Foundation Models for Physical AI cites this paper.

World Simulation with Video Foundation Models for Physical AI On the Importance of Noise Scheduling for Diffusion Models

Reference 15

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arxiv_id, observed 2026-05-12T23:01:13.947275Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-12T23:01:13.546110Z digest=sha256:6446a660a72477ec73475d37ed98daaa6310093cae2b0d16ea1b3676e65237a8

Observation 52508be5-c8ba-4946-9d36-0951af523ac3 · inbound

Back to Basics: Let Denoising Generative Models Denoise cites this paper.

Back to Basics: Let Denoising Generative Models Denoise On the Importance of Noise Scheduling for Diffusion Models

Reference 7

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arxiv_id, observed 2026-05-11T22:16:28.350378Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-11T22:16:26.996599Z digest=sha256:6d403377ee2ccf06ef1983d414de85f164a09154feac27407b4dca1199225a61

Observation d7031c64-1827-49c9-97a3-7a4a7fb8921e · inbound

Trainable Log-linear Sparse Attention for Efficient Diffusion Transformers cites this paper.

Trainable Log-linear Sparse Attention for Efficient Diffusion Transformers On the Importance of Noise Scheduling for Diffusion Models

Reference 3

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no resolver link, observed 2026-08-03T15:35:13.540081Z

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source=pdf_text observed=2026-08-03T15:35:13.540081Z digest=sha256:2203c5f3805c46318c1a222378642a6c9d178c18291903d38ca2926f6e66b2c9

Observation 48748107-7429-4c52-bd16-b9b0e5d1e793 · inbound

Is Monotonic Sampling Necessary in Diffusion Models? cites this paper.

Is Monotonic Sampling Necessary in Diffusion Models? On the Importance of Noise Scheduling for Diffusion Models

Reference 50

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arxiv_id, observed 2026-05-13T07:37:29.331843Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-13T07:35:39.686782Z digest=sha256:fbd5177232be60a35be44b72e734ff482b60d5ecb17adf360af83d11f2c703c7

Observation 3773f44b-653f-4f72-b7db-cfb5cb34256b · inbound

Entropy Across the Bridge: Conditional-Marginal Discretization for Flow and Schr\"odinger Samplers cites this paper.

Entropy Across the Bridge: Conditional-Marginal Discretization for Flow and Schr\"odinger Samplers On the Importance of Noise Scheduling for Diffusion Models

Reference 5

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arxiv_id, observed 2026-05-20T19:48:57.476233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-20T19:46:36.955669Z digest=sha256:f0b5bb1d36ad57692360b623ae7184cda52ea2d5b19f511cfa59180797947430

Observation 06291588-0bab-4846-8a8d-f6ee539c0426 · inbound

WavFlow: Audio Generation in Waveform Space cites this paper.

WavFlow: Audio Generation in Waveform Space On the Importance of Noise Scheduling for Diffusion Models

Reference 3

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verified exact
arxiv_id, observed 2026-05-20T07:38:09.602797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-20T07:33:35.243337Z digest=sha256:52a03b76f2a416a9e0fb6df8530e91aca81f2453eb896a400250d27a04b1f1d7

Observation 8db47675-6c31-4503-9886-b7cf1d0274ad · inbound

Generative Pseudo-Force Fields for Molecular Generation cites this paper.

Generative Pseudo-Force Fields for Molecular Generation On the Importance of Noise Scheduling for Diffusion Models

Reference 72

Resolution
verified exact
arxiv_id, observed 2026-05-20T11:58:15.110958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-20T11:55:36.275835Z digest=sha256:e01bdf2e15a24c6cac50a4d7754afc373f1fd20f38bb78bbba08051b72c1f36b

Observation 67023ac4-11fc-4edb-81ec-11350d1703d4 · inbound

Everything at Every Scale: Scale-Invariant Diffusion with Continuous Super-Resolution cites this paper.

Everything at Every Scale: Scale-Invariant Diffusion with Continuous Super-Resolution On the Importance of Noise Scheduling for Diffusion Models

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-06-29T23:04:02.146652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-29T22:57:34.265472Z digest=sha256:7d31405ea96bd582724c6db2a241c7f7e93abfc6821efcc2805555fe5ada257e

Observation 45f9bd5b-b056-4fff-a1b4-fe1d47b823ae · inbound

WavTTS: Towards High-Quality Zero-Shot TTS via Direct Raw Waveform Modeling cites this paper.

WavTTS: Towards High-Quality Zero-Shot TTS via Direct Raw Waveform Modeling On the Importance of Noise Scheduling for Diffusion Models

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-02T05:16:39.809182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T08:18:42.002083Z digest=sha256:50a531bc1dbd3a3c03541ac9919f7e3aef4f70f11018e8be26b186a989acf5fe

Observation edbf22ef-e2c1-4a7e-908f-29ac3bc129f4 · inbound

Class-frequency Guided Noise Schedule for Diffusion Models cites this paper.

Class-frequency Guided Noise Schedule for Diffusion Models On the Importance of Noise Scheduling for Diffusion Models

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T20:03:56.720421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-29T04:35:43.680865Z digest=sha256:ac453b4d2c03eafd435943ac514d48d80ee9ebb44e934ec50bf39d8d68e5802d

Observation cd4334f6-67f9-4aef-8834-18fdad19b943 · inbound

Steering Optimisation Trajectories in Diffusion Representation Learning cites this paper.

Steering Optimisation Trajectories in Diffusion Representation Learning On the Importance of Noise Scheduling for Diffusion Models

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-07-07T18:04:00.525703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-07-07T17:54:09.140773Z digest=sha256:f9ec973a76f9c3d32cc41dbc8151c395f9af8769ab91a752ed6bc69d54ea14ed

Observation 1310f08a-a403-4fda-8526-7cb0e1c2cf51 · inbound

Detangled: A Framework for Creating, Editing, and Inferencing Feature Rich Hair Strands cites this paper.

Detangled: A Framework for Creating, Editing, and Inferencing Feature Rich Hair Strands On the Importance of Noise Scheduling for Diffusion Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-07-14T15:23:41.787467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:23:41.787467Z digest=sha256:ddba46e1b5dda11432d9402980a11719387092a7495639ea2ba92c1e1d7f5cfd

Observation 94256687-78e5-4743-998d-8d467a0ed576 · inbound

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching cites this paper.

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching On the Importance of Noise Scheduling for Diffusion Models

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-01T11:10:14.313140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T11:10:14.313140Z digest=sha256:680b76afb41c9d50006ecd09cca7c05045ef93028081587b035f9327038ec320

Observation b68a0e41-ba66-4ae1-b522-548b27178d07 · inbound

Twins: Learn to Predict Unified Representations with Focal Loss cites this paper.

Twins: Learn to Predict Unified Representations with Focal Loss On the Importance of Noise Scheduling for Diffusion Models

Reference 232

Resolution
unresolved
no resolver link, observed 2026-08-01T04:30:07.773554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T04:30:07.773554Z digest=sha256:45670f7dc5371cc2ff5089761d4dd09aa9cb4f78039247023e5aae6811dc3f11

Observation 86478c92-20cb-489d-b5c2-840d232ece83 · inbound

Stable Autoregressive Speech Generation with Low-Frame-Rate High-Dimensional Continuous Tokens cites this paper.

Stable Autoregressive Speech Generation with Low-Frame-Rate High-Dimensional Continuous Tokens On the Importance of Noise Scheduling for Diffusion Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-03T08:35:47.701433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T08:35:47.701433Z digest=sha256:7325c7380a0720aebc340586cdc24fe5c672e4e9daabc7441ab1739640678734