Paper Citation Record · LEDGER

Controllable diffusion-based generation for multi-channel biological data

As of 20 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2507.02902.

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

pith.paper-citation-record.v1
2507.02902 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:11:13.624615Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

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External citation measurements

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Outbound references

Observation d0a6d37d-9416-4fef-b983-66c769bcaa2d · outbound

This paper cites High- resolution image synthesis with latent diffusion models.

Controllable diffusion-based generation for multi-channel biological data High- resolution image synthesis with latent diffusion models

Reference 1

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Source-reported events for the cited work

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Observation 5504f73c-c4f2-4a3b-aeca-db11271b70a4 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

Controllable diffusion-based generation for multi-channel biological data Adding conditional control to text-to-image diffusion models

Reference 2

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Observation b9c78982-506f-4337-8cd6-c000738919f3 · outbound

This paper cites Imaging mass cytometry.Cytometry Part A, 91(2):160–169, 2017.

Controllable diffusion-based generation for multi-channel biological data Imaging mass cytometry.Cytometry Part A, 91(2):160–169, 2017

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:17.279450Z

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Observation 0b8c4049-92bb-4173-a51b-f100f6a5323b · outbound

This paper cites Museum of spatial transcriptomics.Nature Methods, 19(5):534–546, 2022.

Controllable diffusion-based generation for multi-channel biological data Museum of spatial transcriptomics.Nature Methods, 19(5):534–546, 2022

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:17.265910Z

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Observation a36e99dd-8f50-45c8-90dc-ebd8477107ff · outbound

This paper cites Generative modeling by estimating gradients of the data distribution.

Controllable diffusion-based generation for multi-channel biological data Generative modeling by estimating gradients of the data distribution

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:17.253868Z

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Observation a9b8bcf0-ba67-4c64-8a79-22865f269f11 · outbound

This paper cites Lee, Jonathan Ho, Tim Salimans, David Fleet, and Mohammad Norouzi.

Controllable diffusion-based generation for multi-channel biological data Lee, Jonathan Ho, Tim Salimans, David Fleet, and Mohammad Norouzi

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:17.240716Z

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Observation 4d28ae92-3e01-4643-b715-7f7dfceb9bcb · outbound

This paper cites Brushnet: A plug-and-play image inpainting model with decomposed dual-branch diffusion.

Controllable diffusion-based generation for multi-channel biological data Brushnet: A plug-and-play image inpainting model with decomposed dual-branch diffusion

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:17.039649Z

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Observation 97488604-9ceb-4432-861e-77675ef93d61 · outbound

This paper cites Weiss, Niru Maheswaranathan, and Surya Ganguli.

Controllable diffusion-based generation for multi-channel biological data Weiss, Niru Maheswaranathan, and Surya Ganguli

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:16.842659Z

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Observation 2fcc6d26-9798-436d-a8af-b2b5c8382f32 · outbound

This paper cites Denoising diffusion probabilistic models.

Controllable diffusion-based generation for multi-channel biological data Denoising diffusion probabilistic models

Reference 9

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Source-reported events for the cited work

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Observation b6a21499-da5b-4b71-981d-5f0058b6077c · outbound

This paper cites Nontexture inpainting by curvature-driven diffusions.Journal of visual communication and image representation, 12(4):436–449, 2001.

Controllable diffusion-based generation for multi-channel biological data Nontexture inpainting by curvature-driven diffusions.Journal of visual communication and image representation, 12(4):436–449, 2001

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:16.479404Z

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Observation f0fb3165-dfda-40f1-a225-2fb892717f13 · outbound

This paper cites Amortized inference in probabilistic reasoning.

Controllable diffusion-based generation for multi-channel biological data Amortized inference in probabilistic reasoning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:16.213644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 99c0e2c1-234e-48c5-89c3-615b493f3e80 · outbound

This paper cites Iterative amortized inference.

Controllable diffusion-based generation for multi-channel biological data Iterative amortized inference

Reference 12

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Observation 229dfd2a-68e6-4bc8-a27c-0f3b0b10062b · outbound

This paper cites Squeeze-and-excitation networks.

Controllable diffusion-based generation for multi-channel biological data Squeeze-and-excitation networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:15.923548Z

Source-reported events for the cited work

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Observation 243b03c4-3b72-4feb-ac6c-f7b9a1b37824 · outbound

This paper cites Diffusion models beat gans on image synthesis.

Controllable diffusion-based generation for multi-channel biological data Diffusion models beat gans on image synthesis

Reference 14

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Observation 3c40edce-35e1-4c5c-a353-30d22f53dcb5 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Controllable diffusion-based generation for multi-channel biological data Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T23:11:12.281058Z

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Observation 7b15fc71-6820-4d49-b60b-4b5587fda96a · outbound

This paper cites Glide: Towards photorealistic image generation and editing with text-guided diffusion models.

Controllable diffusion-based generation for multi-channel biological data Glide: Towards photorealistic image generation and editing with text-guided diffusion models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:15.639586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation db0562a9-8644-4964-9789-40ce75716855 · outbound

This paper cites Classifier-free diffusion guidance.

Controllable diffusion-based generation for multi-channel biological data Classifier-free diffusion guidance

Reference 17

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Source-reported events for the cited work

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Observation 09c39d87-0f32-43e6-874f-f7a490a4f8a6 · outbound

This paper cites Non-isometric codes for the black hole interior from fundamental and effective dynamics.

Controllable diffusion-based generation for multi-channel biological data Non-isometric codes for the black hole interior from fundamental and effective dynamics

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T23:11:12.562018Z

Source-reported events for the cited work

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Observation 1e2a1d87-b623-45c3-85d9-5796735f77e5 · outbound

This paper cites Colorpeel: Color prompt learning with diffusion models via color and shape disentanglement.

Controllable diffusion-based generation for multi-channel biological data Colorpeel: Color prompt learning with diffusion models via color and shape disentanglement

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:15.300080Z

Source-reported events for the cited work

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Observation 22df9b94-dd9b-479a-9863-36765dcf3bdf · outbound

This paper cites A mixture-of-experts deep generative model for integrated analysis of single-cell multiomics data.

Controllable diffusion-based generation for multi-channel biological data A mixture-of-experts deep generative model for integrated analysis of single-cell multiomics data

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:15.162632Z

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Observation cb5399a0-6cda-4717-8aac-21bd5bf1bd6c · outbound

This paper cites Explain- able multi-task learning for multi-modality biological data analysis.Nature Communications, 2024.

Controllable diffusion-based generation for multi-channel biological data Explain- able multi-task learning for multi-modality biological data analysis.Nature Communications, 2024

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:15.070982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e668c989-47ba-4378-893d-a5f3815de9d2 · outbound

This paper cites Predictive modeling of highly multiplexed tumor tissue images by graph neural networks.medRxiv, 2021.

Controllable diffusion-based generation for multi-channel biological data Predictive modeling of highly multiplexed tumor tissue images by graph neural networks.medRxiv, 2021

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:14.957648Z

Source-reported events for the cited work

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Observation caa69b7a-2634-4601-84c2-7271606168f7 · outbound

This paper cites Diffusion generative modeling for spatially resolved gene expression inference from histology images.

Controllable diffusion-based generation for multi-channel biological data Diffusion generative modeling for spatially resolved gene expression inference from histology images

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:14.810779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 681e1eae-9fb9-4617-9d42-ab2fcdd7678d · outbound

This paper cites Integrated analysis of multimodal single-cell data.Cell, 184(13):3573–3587, 2021.

Controllable diffusion-based generation for multi-channel biological data Integrated analysis of multimodal single-cell data.Cell, 184(13):3573–3587, 2021

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:14.697024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 09029812-ef70-4767-b4e7-247281310b52 · outbound

This paper cites Simultaneous epitope and transcriptome measurement in single cells.Nature methods, 14(9):865–868, 2017.

Controllable diffusion-based generation for multi-channel biological data Simultaneous epitope and transcriptome measurement in single cells.Nature methods, 14(9):865–868, 2017

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T23:11:13.039011Z

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Observation eebce0ae-fe2a-4e21-b7d3-f17a2e83dd50 · outbound

This paper cites Luecken, Daniel B.

Controllable diffusion-based generation for multi-channel biological data Luecken, Daniel B

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:14.569752Z

Source-reported events for the cited work

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Observation d58b66b9-f766-40d0-84e9-b4e8183ac8e7 · outbound

This paper cites A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation.Blood, The Journal of the American Society of Hematology, 128(8):e20–e31, 2016.

Controllable diffusion-based generation for multi-channel biological data A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation.Blood, The Journal of the American Society of Hematology, 128(8):e20–e31, 2016

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:14.465984Z

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Observation 9177b2f0-d7dc-4a24-9e4f-523add4ebd85 · outbound

This paper cites Gabitto, Rohan V.

Controllable diffusion-based generation for multi-channel biological data Gabitto, Rohan V

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:14.361367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a88fee12-1788-44bf-95bd-e86eafec0726 · outbound

This paper cites Multi-omics single-cell data integration and regulatory inference with graph-linked embedding.Nature Biotechnology, 40, 2022.

Controllable diffusion-based generation for multi-channel biological data Multi-omics single-cell data integration and regulatory inference with graph-linked embedding.Nature Biotechnology, 40, 2022

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:14.265632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7e5e44fa-de27-446c-9cdb-e0e1f9ef2573 · outbound

This paper cites Score identity distillation: Exponentially fast distillation of pretrained diffusion models for one-step generation.

Controllable diffusion-based generation for multi-channel biological data Score identity distillation: Exponentially fast distillation of pretrained diffusion models for one-step generation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:14.132591Z

Source-reported events for the cited work

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Observation a6bbeb58-3243-4be0-aab9-58a159292a5d · outbound

This paper cites Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step.

Controllable diffusion-based generation for multi-channel biological data Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T23:11:13.453218Z

Source-reported events for the cited work

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Observation 7a721f23-54ee-4693-a838-bea4c2ae4a25 · outbound

This paper cites Acqui- sition of discrete immune suppressive barriers contributes to the initiation and progression of preinvasive to invasive human lung cancer.bioRxiv, pages 2024–12, 2025.

Controllable diffusion-based generation for multi-channel biological data Acqui- sition of discrete immune suppressive barriers contributes to the initiation and progression of preinvasive to invasive human lung cancer.bioRxiv, pages 2024–12, 2025

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:14.045450Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 670e08d5-3ce7-4096-ad4f-98b581ef5e89 · outbound

This paper cites The single-cell pathology landscape of breast cancer.Nature, 578(7796):615–620, 2020.

Controllable diffusion-based generation for multi-channel biological data The single-cell pathology landscape of breast cancer.Nature, 578(7796):615–620, 2020

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:13.918580Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 046f8b08-7a77-496e-b519-7c048db0bc46 · outbound

This paper cites High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis.Nature Communications, 14(1):8353, 2023.

Controllable diffusion-based generation for multi-channel biological data High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis.Nature Communications, 14(1):8353, 2023

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:13.807410Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.