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Paper Citation Record · LEDGER

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster

As of 12 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2605.18204.

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

pith.paper-citation-record.v1
2605.18204 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-20T00:26:58.820675Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

18 of 18 outbound references displayed

  • verified exact11
  • verified fuzzy4
  • unresolved0
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 60154b48-0d34-4e0f-b509-4d65a2974b68 · outbound

This paper cites librosa/librosa: 0.6.3.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster librosa/librosa: 0.6.3

Reference 1

Resolution
malformed identifier
doi_truncated, observed 2026-05-20T00:27:53.441279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:9376ccb7f7a1730d2d0be6ea5861885010f733c3f78b4f03961b8b3892207305

Observation b8feefa0-e895-4b3d-a315-ab0a53fb6452 · outbound

This paper cites DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-20T06:50:38.345995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:a8c6a6175c7e55e5205914d8b7820b59af36993d6e925a6b26bcf3ade847216b

Observation b0a80db6-1677-4602-8710-766988ebb132 · outbound

This paper cites Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-20T00:27:53.618112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:c7e4d374095239190522d3663633e2b6a3c0697da16a523836a31dabc8779c8f

Observation 0184025c-2532-4360-997f-7e7a0ff2211e · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster Categorical Reparameterization with Gumbel-Softmax

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-05-20T00:27:53.573837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:14a60a4bbcbc8f1f04aaee26db23b68df4cd571444435aecd9487850d47161ec

Observation 3eba1d1f-603b-4233-8de0-f482e5305ba1 · outbound

This paper cites Meng Liu, Keqiang Yan, Bora Oztekin, and Shuiwang Ji.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster Meng Liu, Keqiang Yan, Bora Oztekin, and Shuiwang Ji

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T00:27:54.052032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:3318243fed682ebe5cb465dc86cd2b1dff810a23b6258441ef4253aba540eab6

Observation 2eb311e3-0fc4-43ed-b8ed-d80742b98485 · outbound

This paper cites Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-05-20T00:27:53.603689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:a7e7391ca2fdd200203fb895b64360ce571a3243d57ba5c708cf554db984b0fb

Observation b51f5a43-acef-4413-8d55-c9e3b88017bc · outbound

This paper cites The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-05-20T00:27:53.597375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:58aa4075e5f48a60e3e960b20389e11e25eccbd459aec3c960c1012bfe1f3ebe

Observation 813d5fb0-b8c2-497d-9b20-c05e791ede55 · outbound

This paper cites TESS: Text-to-Text Self-Conditioned Simplex Diffusion.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster TESS: Text-to-Text Self-Conditioned Simplex Diffusion

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-20T00:27:53.624849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:66028508b96fd048a1fb44bbd16acbc882a03bf3c26f7b3da1b3e58d6e58a469

Observation 0cbfb68c-659d-432d-b241-514733846a30 · outbound

This paper cites Compressed and smooth latent space for text diffusion modeling.arXiv preprint arXiv:2506.21170.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster Compressed and smooth latent space for text diffusion modeling.arXiv preprint arXiv:2506.21170

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-20T00:27:53.560342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:3c17cb4f3ed08f7bb2cb1ced627ca92761cb13638ea614bbb88f76e087276968

Observation 4841fb82-e49a-4b44-8ed2-75aa672d89a8 · outbound

This paper cites A corpus and cloze evaluation for deeper understanding of commonsense stories.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster A corpus and cloze evaluation for deeper understanding of commonsense stories

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T00:27:54.064859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:6732f2981dc6f16b3a710241ea0020973c8461ae6b5349ef9b39d86ed5e07745

Observation 016b8cf2-0133-41aa-855e-23e614997886 · outbound

This paper cites Simplified and Generalized Masked Diffusion for Discrete Data.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster Simplified and Generalized Masked Diffusion for Discrete Data

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-20T00:27:53.567554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:54da7fbea2cf389414dc05c922997ecbb992a36775cba0958c8f46c7052c59dc

Observation d9d3f48f-1572-47d4-bc1c-43321c405e57 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 13

Resolution
metadata mismatch
local_arxiv, observed 2026-05-20T00:27:53.590309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:f58182f85ad0870fa2452fa3af67055bb2d46026f45410d5aa5ff5cd818ca310

Observation 911e1f3c-9e4a-4745-80e6-9f0f2dfe7a01 · outbound

This paper cites Learning-Order Autoregressive Models with Application to Molecular Graph Generation.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster Learning-Order Autoregressive Models with Application to Molecular Graph Generation

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-20T00:27:53.551060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:2b524c1da74cbd7861f1f8d016e886c67e79d491d211bd1d7b52ce49a2c60cf3

Observation 2a003d31-70e9-4b86-bdab-2c41e7cb1da5 · outbound

This paper cites Williams.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster Williams

Reference 15

Resolution
metadata mismatch
doi, observed 2026-05-20T00:27:53.423988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:862cea58b585057284095ed7d3ed09e4e6274f847f48ce80909022a0c7e8224a

Observation ced87f62-1a04-4cac-82c5-eec3723bf6bb · outbound

This paper cites One-step Diffusion Models with $f$-Divergence Distribution Matching.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster One-step Diffusion Models with $f$-Divergence Distribution Matching

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-20T00:27:53.611179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:53c707cd305c427ed2f8f9f13cff2df4d24ee3829838da618c6620fb594a0c16

Observation 018f0eb5-4840-4495-9fd6-8bb44ebedb11 · outbound

This paper cites SeqDiffuSeq: Text Diffusion with Encoder-Decoder Transformers.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster SeqDiffuSeq: Text Diffusion with Encoder-Decoder Transformers

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-20T00:27:53.542455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:8c6c4ab06cffe69b4dd95c6adbe8ab60cdcaad03fc0bffae51878de23f24c5b2

Observation d0ec821d-c8ce-4f4c-a996-d7effd943ca7 · outbound

This paper cites (2019); Luo et al.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster (2019); Luo et al

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T00:27:54.060412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:6f0cabca057495452c426d65bf3e403898144afeb98dc16e66a32af2282ef6cd

Observation 13c93969-6ded-493a-8833-e61827c2cad2 · outbound

This paper cites (2023) with6layers and6heads and an embedding size of512to parameterize the model, and a pretrained GPT-2 for PPL calculation.

Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster (2023) with6layers and6heads and an embedding size of512to parameterize the model, and a pretrained GPT-2 for PPL calculation

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-05-20T00:27:54.056526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T00:26:58.820675Z digest=sha256:8014ef857173441db16732ccfe14cebed33c0f30bfc6d2a96751f65130fcd996

Pith citing papers

No inbound Pith citation observations are available.