Paper Citation Record · LEDGER

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation

As of 15 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.20545.

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

pith.paper-citation-record.v1
2607.20545 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T06:58:57.330836Z

measured 33 of 33 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 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

33 of 33 outbound references displayed

verified exact0
verified fuzzy0
unresolved32
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b3a6422-5991-4cbc-bbdd-27d3796e1f1b · outbound

This paper cites Sana-sprint: One-step diffusion with continuous-time consistency distillation.arXiv preprint arXiv:2503.09641, 2025.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Sana-sprint: One-step diffusion with continuous-time consistency distillation.arXiv preprint arXiv:2503.09641, 2025

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:53.089792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1a582a4-faad-4020-9197-d307c1d0aa85 · outbound

This paper cites On the constrained time-series generation problem.Advances in Neural Information Processing Systems, 36:61048–61059, 2023.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation On the constrained time-series generation problem.Advances in Neural Information Processing Systems, 36:61048–61059, 2023

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:53.179816Z

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Observation 9aa3b8e5-3c84-4bfd-90da-b32a0c221866 · outbound

This paper cites EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:53.265901Z

Source-reported events for the cited work

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Observation 34e23369-156f-4738-97c8-a3fbc3689323 · outbound

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

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:53.357451Z

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Unavailable: canonical work link unavailable.

Observation c316c677-d3d8-4aac-94eb-7a1026ab0fbe · outbound

This paper cites Elucidating the design space of diffusion-based generative models.Advances in neural information processing systems, 35: 26565–26577, 2022.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Elucidating the design space of diffusion-based generative models.Advances in neural information processing systems, 35: 26565–26577, 2022

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:53.497873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fd6f928-0d6c-409e-9d94-a050b30417af · outbound

This paper cites Diffwave: A versatile diffusion model for audio synthesis.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Diffwave: A versatile diffusion model for audio synthesis

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:53.659598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf55c5e0-c4c7-43f0-85d9-8b8fedfcd8af · outbound

This paper cites Beta sampling is all you need: Efficient image generation strategy for diffusion models using stepwise spectral analysis.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Beta sampling is all you need: Efficient image generation strategy for diffusion models using stepwise spectral analysis

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:53.865579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09f98c7c-92ac-4939-a43d-5ae924cd7770 · outbound

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

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Distrifusion: Distributed parallel inference for high-resolution diffusion models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:54.052822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbe3b10b-63bc-4a04-b6ae-82771e8b5d56 · outbound

This paper cites Faster diffusion: Rethinking the role of the encoder for diffusion model inference.Advances in Neural Information Processing Systems, 37: 85203–85240, 2024.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Faster diffusion: Rethinking the role of the encoder for diffusion model inference.Advances in Neural Information Processing Systems, 37: 85203–85240, 2024

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:54.171938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 333953ca-4d55-4c60-85b7-e97425716b2f · outbound

This paper cites Q-dm: An efficient low-bit quantized diffusion model.Advances in neural information processing systems, 36: 76680–76691, 2023.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Q-dm: An efficient low-bit quantized diffusion model.Advances in neural information processing systems, 36: 76680–76691, 2023

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:54.268673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 005e088f-50ab-4961-addb-6df258b3b91a · outbound

This paper cites Timestep embedding tells: It’s time to cache for video diffusion model.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Timestep embedding tells: It’s time to cache for video diffusion model

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:54.334298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcc0336a-ff18-48e0-8d0c-b369de3ed164 · outbound

This paper cites Retrieval-augmented diffusion models for time series forecasting.Advances in Neural Information Processing Systems, 37:2766–2786, 2024.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Retrieval-augmented diffusion models for time series forecasting.Advances in Neural Information Processing Systems, 37:2766–2786, 2024

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:54.388084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0eb1d0e-0d2c-4aab-b3fe-6357c74a9ee1 · 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.

StrideDiffusion: Accelerating Diffusion Models for Time-series 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

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:54.455656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a73164d3-fc90-42ac-82a2-43212906231a · outbound

This paper cites Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models.Machine Intelligence Re- search, pages 1–22, 2025.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models.Machine Intelligence Re- search, pages 1–22, 2025

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:54.527226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1754728d-a3c3-4d2c-ba87-537fab8d7c29 · outbound

This paper cites Deepcache: Accelerating diffusion models for free.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Deepcache: Accelerating diffusion models for free

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:54.664152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2be6093-6db0-4f04-a7d3-3b85fac772d2 · outbound

This paper cites Leapfrog diffusion model for stochastic trajectory prediction.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Leapfrog diffusion model for stochastic trajectory prediction

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:54.776911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 638567e5-b69c-42fe-a76c-4cc9408643a0 · outbound

This paper cites Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:55.038172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2042dc83-5e62-4250-a7a3-6080fa3a281a · outbound

This paper cites Generative Modelling With Inverse Heat Dissipation.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Generative Modelling With Inverse Heat Dissipation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:55.251729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cdf3eb2-93a8-45d9-bbbf-6308f60eabd7 · outbound

This paper cites Progressive distillation for fast sampling of diffusion models.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Progressive distillation for fast sampling of diffusion models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:55.349465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05b0f852-dec4-4c83-b499-09dc4f801824 · outbound

This paper cites Non-autoregressive Conditional Diffusion Models for Time Series Prediction.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Non-autoregressive Conditional Diffusion Models for Time Series Prediction

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:55.475862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cd2f7a5-2a98-420d-b94b-2fa5aebd123a · outbound

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

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Temporal dynamic quantization for diffusion models.Advances in neural information processing systems, 36:48686–48698, 2023

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:55.573210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4af7db5-404c-4e2a-80a5-0aa1526052f6 · outbound

This paper cites Denoising Diffusion Implicit Models.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Denoising Diffusion Implicit Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:55.671463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f94abf21-6b46-4d4b-9698-742fe1765e79 · outbound

This paper cites Csdi: Conditional score-based diffusion models for probabilistic time series imputation.Advances in neural information processing systems, 34:24804–24816, 2021.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Csdi: Conditional score-based diffusion models for probabilistic time series imputation.Advances in neural information processing systems, 34:24804–24816, 2021

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:55.774089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c471d7aa-3219-4f47-80af-1e91aadd98ec · outbound

This paper cites VideoLCM: Video Latent Consistency Model.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation VideoLCM: Video Latent Consistency Model

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:55.991889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52173577-2645-47a4-9f89-6db526d04d7f · outbound

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

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Cache me if you can: Accelerating diffusion models through block caching

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:56.133387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7927b78c-7016-4137-be80-019a7e12e13f · outbound

This paper cites Diffusion probabilistic model made slim.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Diffusion probabilistic model made slim

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:56.296839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5beedfd-b994-4fd9-853f-89807c0381b1 · outbound

This paper cites Non-stationary Diffusion For Probabilistic Time Series Forecasting.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Non-stationary Diffusion For Probabilistic Time Series Forecasting

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:56.446967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09d8e498-41a7-4ad7-9e64-71df851cf2c2 · outbound

This paper cites Time-series generative adversarial networks.Advances in neural information processing systems, 32, 2019.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Time-series generative adversarial networks.Advances in neural information processing systems, 32, 2019

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:56.632948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99e9822d-6e8d-4a71-b93a-9625089e4326 · outbound

This paper cites Dmfft: improving the generation quality of diffusion models using fast fourier transform.Scientific Reports, 15(1):10200, 2025.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Dmfft: improving the generation quality of diffusion models using fast fourier transform.Scientific Reports, 15(1):10200, 2025

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:56.813501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9fbb151-e688-4c69-8891-37f687cccba4 · outbound

This paper cites Diffusion-ts: Interpretable diffusion for general time series genera- tion.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Diffusion-ts: Interpretable diffusion for general time series genera- tion

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:56.992856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ab344b1-25ea-4218-a538-c38ef68b6ecd · outbound

This paper cites FreqPrior: Improving Video Diffusion Models with Frequency Filtering Gaussian Noise.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation FreqPrior: Improving Video Diffusion Models with Frequency Filtering Gaussian Noise

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:57.044175Z

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Unavailable: canonical work link unavailable.

Observation 7d705a7b-d59e-4cd5-a013-e6c2121efc0d · outbound

This paper cites Limitations.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Limitations

Reference 32

Resolution: malformed identifier; no resolver link, observed 2026-08-02T06:58:57.233207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b880204-d475-43f8-b9a4-0dab569a6341 · outbound

This paper cites Guidelines: • The answer [N/A] means that the paper does not involve crowdsourcing nor research with human subjects.

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation Guidelines: • The answer [N/A] means that the paper does not involve crowdsourcing nor research with human subjects

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T06:58:57.330836Z

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Pith citing papers

No inbound Pith citation observations are available.