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Paper Citation Record · LEDGER

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models

As of 12 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2501.08180.

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

pith.paper-citation-record.v1
2501.08180 v2

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:34:22.510102Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

19 of 19 outbound references displayed

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  • verified fuzzy2
  • unresolved17
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bfc4e646-050e-4276-bfd0-caefd066bfcf · outbound

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

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models

Reference 4

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source=pdf_text observed=2026-08-10T20:34:22.445317Z digest=sha256:d6fbdf6f77fe289ac184172e6d3c20d5bc2b7998bccedf7b9e5b49fe0a7843eb

Observation 8863fb84-aa8c-4442-8886-8f8335a293db · outbound

This paper cites On Fast Sampling of Diffusion Probabilistic Models.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models On Fast Sampling of Diffusion Probabilistic Models

Reference 6

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source=pdf_text observed=2026-08-10T20:34:22.453961Z digest=sha256:218bb4434181aabbe04ab2f94c442df38e3117083f199344953b6cd3e71465c4

Observation 009670b9-68da-41db-ae51-4adc74f44e65 · outbound

This paper cites bioRxiv, 2022–07.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models bioRxiv, 2022–07

Reference 7

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raw_fallback, observed 2026-08-10T20:34:22.738237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:34:22.458485Z digest=sha256:a2b77c9276fc343befe813a40e4cb057d0aa0ab8997f44d45351c3a6a6fe19eb

Observation edb90a5b-65a5-4da9-8e6a-89070aacac59 · outbound

This paper cites BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction

Reference 8

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source=pdf_text observed=2026-08-10T20:34:22.462470Z digest=sha256:a104fb1f2862ce3ec9dd76957672817e13a7690f57405c678227c97482f81033

Observation 369157e2-d472-4a33-ae88-d202dad747d8 · outbound

This paper cites AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Reference 9

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source=pdf_text observed=2026-08-10T20:34:22.466420Z digest=sha256:ce3d9087fdcaa8e49b19a7568fbd9ea36a92f56a652a277243a73739484550de

Observation 8a627873-20c5-44a9-b7fd-15a6fe974038 · outbound

This paper cites Pseudo Numerical Methods for Diffusion Models on Manifolds.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models Pseudo Numerical Methods for Diffusion Models on Manifolds

Reference 10

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source=pdf_text observed=2026-08-10T20:34:22.469989Z digest=sha256:1f90c9837096f2e23553b7d9d1d3bdbee15f1921c33fe508dc851374914e72e9

Observation 7c568047-da76-4695-b5e3-eb199ddd0cba · outbound

This paper cites A White Paper on Neural Network Quantization.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models A White Paper on Neural Network Quantization

Reference 11

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source=pdf_text observed=2026-08-10T20:34:22.474471Z digest=sha256:248df1c5d747a13ba7cfb7364ab9456b3898382713f5df554788c0c9b6f3ed6e

Observation fae40b67-5033-41bb-b3f5-fdfd346ee41a · outbound

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

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models Progressive Distillation for Fast Sampling of Diffusion Models

Reference 12

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source=pdf_text observed=2026-08-10T20:34:22.478604Z digest=sha256:a3868e6df4511a229112f0e494731a09bc9c27533ddc4b539cc592325bc2ed7e

Observation 49fab3b0-b6ba-451d-b9ec-f9c9cb0808df · outbound

This paper cites InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1972–1981.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1972–1981

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:34:22.725943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:34:22.483185Z digest=sha256:70a172352c6a8dc01b5e9be8f9ae13785ba2d452ccda220e6781837166e87f27

Observation 78c8ad39-5e28-4eeb-bdff-246ff2b912cd · outbound

This paper cites Make-A-Video: Text-to-Video Generation without Text-Video Data.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models Make-A-Video: Text-to-Video Generation without Text-Video Data

Reference 14

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source=pdf_text observed=2026-08-10T20:34:22.488364Z digest=sha256:ef700d4560709be9eaabb972f649994a92cd9481be0f15fbcdd0b332d8eeda54

Observation b904f35d-9cb2-485b-af68-151a4b5f2944 · outbound

This paper cites Consistency Models.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models Consistency Models

Reference 15

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source=pdf_text observed=2026-08-10T20:34:22.492444Z digest=sha256:693bb38793b0ca18036940cac6e3b055b05ac693dab85c5db801c3ff6349dccb

Observation 782af067-6e06-41cc-8f3d-5374016899dc · outbound

This paper cites SinSR: Diffusion-Based Image Super-Resolution in a Single Step.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models SinSR: Diffusion-Based Image Super-Resolution in a Single Step

Reference 17

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source=pdf_text observed=2026-08-10T20:34:22.502129Z digest=sha256:360e6f3bb53b04b44a6f7c207d0369238d8dd014c339374cc5531da3c9c3c245

Observation 065b220b-8c24-4286-ad48-6bbef804e4db · outbound

This paper cites QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models QDrop: Randomly Dropping Quantization for Extremely Low-bit Post-Training Quantization

Reference 18

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source=pdf_text observed=2026-08-10T20:34:22.505915Z digest=sha256:875a968b8ff5f9c2bc3662e49bac30f9e2e20897d0e4ad3517de27d08e5b7e7f

Observation a3bd9d07-851c-42a5-a02d-8effa912d449 · outbound

This paper cites Auto-Encoding Variational Bayes.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models Auto-Encoding Variational Bayes

Reference 2013

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source=pdf_text observed=2026-08-10T20:34:22.449925Z digest=sha256:a820e62298c0eb1d6bcabb997e1204748617e633b3cf35606d9ce112335f843a

Observation f31085bc-6983-43be-9908-17ad5ff976e3 · outbound

This paper cites LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

Reference 2015

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source=pdf_text observed=2026-08-10T20:34:22.510102Z digest=sha256:aaf22a3af8430754f06ede516d3308d98b659c65f9c8d5946b8e627fc53e3e7a

Observation 422e85aa-dc08-43bc-8ec6-4e6badadb0b1 · outbound

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

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models Score-Based Generative Modeling through Stochastic Differential Equations

Reference 2020

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source=pdf_text observed=2026-08-10T20:34:22.497024Z digest=sha256:82bfc4b54cadd75f50a241b6b1cfff8b6b770e70e3ed741a63deebf292b81e1a

Observation 42d5dba6-c0b7-4a4d-9d8d-6e84eebf3b9e · outbound

This paper cites Score-Based Generative Modeling with Critically-Damped Langevin Diffusion.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models Score-Based Generative Modeling with Critically-Damped Langevin Diffusion

Reference 2021

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source=pdf_text observed=2026-08-10T20:34:22.440824Z digest=sha256:f89f91791e6ce85c6332025d758edb6dc686f20e5da47c50443802c1e6affdb8

Observation b5f32e2b-24b0-42b5-8ffd-e959b2c11d34 · outbound

This paper cites Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models

Reference 2022

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source=pdf_text observed=2026-08-10T20:34:22.432069Z digest=sha256:22cb9518de87f82f80a6feb7468178eb6aa9129f8674a700ff215bb8b11ee6e1

Observation f552b731-c426-4de9-84ee-db2b87995a90 · outbound

This paper cites TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation.

D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation

Reference 2023

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source=pdf_text observed=2026-08-10T20:34:22.436799Z digest=sha256:9d19e62d1e2cf13e345b66fb5c05bcba10db7a2d57c46232026523bc4dc95d28

Pith citing papers

No inbound Pith citation observations are available.