Pith. sign in

Paper Citation Record · LEDGER

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization

As of 8 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 1 inbound Pith citation observation for arXiv:2510.04961.

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

pith.paper-citation-record.v1
2510.04961 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T11:25:36.104805Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T04:18:45.403718Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T04:20:19.343984Z

Reference resolution

24 of 24 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation afd23de3-b2cc-4395-9129-b0f4404e7310 · outbound

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

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Cosmos World Foundation Model Platform for Physical AI

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:33.514720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:33.514720Z digest=sha256:c4e6f50099a374a43f0926a6d472409a8ca71ed8285d7545dbf1a9d89be7dd8a

Observation bf31865b-3481-4483-b7ff-9cedb76ac3ae · outbound

This paper cites Models directly trained at128×128.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Models directly trained at128×128

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:36.104805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:36.104805Z digest=sha256:abc2f2d9768eef6a56f4b7023243584bf10d64b80544abf61980974e0db0c1e8

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

This paper cites On the Importance of Noise Scheduling for Diffusion Models.

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

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:33.852695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:33.852695Z digest=sha256:171b618a2613392c7d154b7abffb975ed8e5d525531cb7ec973b6a29a4ad2e7d

Observation 991313a8-36de-40d4-8e9d-caa704b7b1c5 · outbound

This paper cites Mixture-of-transformers: A sparse and scalable architecture for multi-modal foundation models.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Mixture-of-transformers: A sparse and scalable architecture for multi-modal foundation models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:34.320465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:34.320465Z digest=sha256:931fed3bfa667f95d8b791a2e58e7cf91c65c5261c0f378bad35e30f72affa87

Observation d9beb344-1cc4-48c0-81b3-3e989b95ed57 · outbound

This paper cites DGAE: Diffusion-guided autoencoder for efficient latent representation learning.arXiv preprint, 2506.09644,.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization DGAE: Diffusion-guided autoencoder for efficient latent representation learning.arXiv preprint, 2506.09644,

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:34.405950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:34.405950Z digest=sha256:42caa21a64c62ef242433eb069891cf442a35a23bfc3758152f9bb4d34250804

Observation 1a665255-829a-4519-992c-b7ddce89f401 · outbound

This paper cites Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:34.483894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:34.483894Z digest=sha256:1adf256c509d72acc952f2685fde15d0ea140c80541a5cb5825ec2332416701f

Observation 6b362679-350b-45dc-a69e-b4c80fd4f4b8 · outbound

This paper cites Movie Gen: A Cast of Media Foundation Models.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Movie Gen: A Cast of Media Foundation Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:34.677649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:34.677649Z digest=sha256:6a2d5706142c3bf09e4953e6621e10a9e9fe472bdf291b69d4faba25eac58f67

Observation 5d542e41-4086-4bba-b548-3d1251fc1e4a · outbound

This paper cites DiVAE: Photorealistic Images Synthesis with Denoising Diffusion Decoder.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization DiVAE: Photorealistic Images Synthesis with Denoising Diffusion Decoder

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:34.998830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:34.998830Z digest=sha256:4ef08048b3bb4b1dc44032a9a6bab2256036999498ce32e5e80351c365e1aa21

Observation c3d31ada-40d1-498a-aa91-1451e099ad77 · outbound

This paper cites Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:35.126850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:35.126850Z digest=sha256:1bbc6fe3091e2a7cb55e858a02aab3de17e91f599c0d61c08fd0b389b54474f7

Observation d897b9ba-f9e8-45c0-924f-f3213b0b7702 · outbound

This paper cites Chameleon: Mixed-Modal Early-Fusion Foundation Models.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:35.251399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:35.251399Z digest=sha256:1942a3181934e733d8ae1aee3a3efa84cda34ee47ee13cd1dfca3c568dabb897

Observation 5c813ace-5135-4c5e-9136-b92ce70c1b66 · outbound

This paper cites Latent denoising makes good visual tokenizers.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Latent denoising makes good visual tokenizers

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:35.389368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:35.389368Z digest=sha256:0cb90106613f8c8006a54ac76bd6d1bb8ce3782bc708da09e3e5d286ba729d2a

Observation 5d1ba256-33da-4e8c-80f3-800dab3f237a · outbound

This paper cites Randomized Autoregressive Visual Generation.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Randomized Autoregressive Visual Generation

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:35.474279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:35.474279Z digest=sha256:c55b2f655e49455e6ea62a0aadcd4fbd2dde55a060cf5e6a4c788606ee728fac

Observation c7c18563-f116-4d62-a1c5-a2eab0d2727d · outbound

This paper cites Z x∈E−1(z) ∆(x,ˆy) # P(D g(z) =y)dydx(2) = min ˆy.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Z x∈E−1(z) ∆(x,ˆy) # P(D g(z) =y)dydx(2) = min ˆy

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:35.579729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:35.579729Z digest=sha256:88044c72ef1ceac2ced5800e9109be13f2f52fb9c146d68b3323de0154f8aeb6

Observation e7ac77c7-ae75-473f-a99b-15c2c20f68a3 · outbound

This paper cites Impact of sampling steps on reconstruction.Quality of samples from diffusion models usually improves with a higher number of sampling steps.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Impact of sampling steps on reconstruction.Quality of samples from diffusion models usually improves with a higher number of sampling steps

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:35.830861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:35.830861Z digest=sha256:254946697820f1517d987333bd78494dc70f64541285e0bfbd962a0feb97826a

Observation 94e3542a-068c-41ff-b080-80403a152ea8 · outbound

This paper cites We show in Table S3 that SSDDoutperforms the original decoders on reconstruction performance, despite being conditioned on features optimized for a different architecture.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization We show in Table S3 that SSDDoutperforms the original decoders on reconstruction performance, despite being conditioned on features optimized for a different architecture

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:35.988569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:35.988569Z digest=sha256:cf270875ed0d0b5524fb2b40e23dd7645a5b937ff3dbcb3cf3e3e5bf3d259e98

Observation 586244c7-883b-4b3c-843e-d4df2de85647 · outbound

This paper cites Classifier-free diffusion guidance.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Classifier-free diffusion guidance

Reference 2006

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:34.036258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:34.036258Z digest=sha256:ef42f9d6bcd0e54eaae13596d04325207082dc1da761ad96d866f5774504ac6b

Observation f1afc006-9434-4351-b0d9-5f3f98801ddb · outbound

This paper cites We use the following loss coefficients: λLPIPS = 0 .5, λREPA = 0 .25, λKL = 10 −6.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization We use the following loss coefficients: λLPIPS = 0 .5, λREPA = 0 .25, λKL = 10 −6

Reference 2009

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:35.709669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:35.709669Z digest=sha256:7d5b75e6f02270a17298c03aeb17e9a536e9981a42c3ead96ef81907dd7aadff

Observation 55b8f0bb-8bca-4482-a8cd-ef7cee9acb91 · outbound

This paper cites GLU Variants Improve Transformer.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization GLU Variants Improve Transformer

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:34.878371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:34.878371Z digest=sha256:d8402f9426b84f85d0ec3e9d7b86c04c5837a8af812569b19cc81a7944b78618

Observation cd865685-340e-41a1-8847-db8730428d08 · outbound

This paper cites High-Fidelity Image Compression with Score-based Generative Models.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization High-Fidelity Image Compression with Score-based Generative Models

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:34.201290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:34.201290Z digest=sha256:b40d16ad4f63a3dc407bf673b50273cb608613f81b42108a3bcd2c08a7a1ed66

Observation f9683d53-1770-4b88-8d04-dfc80b613961 · outbound

This paper cites Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:34.567462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:34.567462Z digest=sha256:834ed78b87e0a74f0ed1a4ff4a75f7b8293d960e4277349096f768abbf57438a

Observation d42dc319-f30f-40b2-9cb9-684040991e75 · outbound

This paper cites Flow to the mode: Mode-seeking diffusion autoencoders for state-of-the-art image tokenization.arXiv preprint, 2503.11056,.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Flow to the mode: Mode-seeking diffusion autoencoders for state-of-the-art image tokenization.arXiv preprint, 2503.11056,

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:34.811180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:34.811180Z digest=sha256:e151ebff7461d33cf29552da3fd9a90caa32b4f5e63880e79ec4f37aedccdcf9

Observation 918554f6-a36e-4b25-801b-a7567b8d98a5 · outbound

This paper cites Diffusion Autoencoders are Scalable Image Tokenizers.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Diffusion Autoencoders are Scalable Image Tokenizers

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:33.951411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:33.951411Z digest=sha256:37fb9b3bfe3ba0271d47f4af1ac1faf76a15ee8f8c1808c8fe48bf3795554355

Observation 807130a9-b35f-43ca-885e-fa91186cda13 · outbound

This paper cites an unresolved cited work.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Unresolved cited work

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:33.726998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:33.726998Z digest=sha256:e7ff04106b0182227f3f5effc4d8cdf13b555351085c305671f667ef352cb12e

Observation 63759571-4e80-45c6-87d2-dd4fae17b2a6 · outbound

This paper cites Imagen 3.arXiv preprint, 2408.07009,.

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization Imagen 3.arXiv preprint, 2408.07009,

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-04T11:25:33.604375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:25:33.604375Z digest=sha256:f880e9ae06cb26bd22eda8e24c8740ade239e36a021df529d0e420ea4d542530

Pith citing papers

Observation cdd01faf-e136-481a-a2c1-0ce84f24032e · inbound

PiD: Fast and High-Resolution Latent Decoding with Pixel Diffusion cites this paper.

PiD: Fast and High-Resolution Latent Decoding with Pixel Diffusion SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-06-30T03:18:05.272041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-25T04:18:45.403718Z digest=sha256:c5e2f97197f7df90b9e6ed54b88b2be18a8d4873207a7805b9b58ee6c7c47723