Paper Citation Record · LEDGER

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application

As of 7 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2506.05710.

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

pith.paper-citation-record.v1
2506.05710 v3

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:19:35.465967Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:57:12.297429Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T19:57:12.409064Z

Reference resolution

41 of 41 outbound references displayed

verified exact1
verified fuzzy21
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ae5b6403-fa9b-432d-89d9-7eb053673457 · outbound

This paper cites What should 6G be?.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application What should 6G be?

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:39.881217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b7577093-7f01-46ce-be09-1fc63fd17e1f · outbound

This paper cites Intellicise wireless networks from semantic communications: A survey, research issues, and challenges,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Intellicise wireless networks from semantic communications: A survey, research issues, and challenges,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:39.573908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 03f9e475-7e2e-46ac-8408-b5c5dd61ddcc · outbound

This paper cites Toward immersive communications in 6G,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Toward immersive communications in 6G,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:39.339894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c5243f26-18b5-4c5a-835c-8d534f75dd47 · outbound

This paper cites Industrial internet of things: Challenges, opportunities, and directions,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Industrial internet of things: Challenges, opportunities, and directions,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:39.062597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation afab465a-759b-4421-a485-f3b6184dc880 · outbound

This paper cites Toward enhanced reinforcement learning-based resource management via digital twin: Opportunities, applications, and challenges,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Toward enhanced reinforcement learning-based resource management via digital twin: Opportunities, applications, and challenges,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:38.822864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2ae783f9-8977-473b-855a-6d7b768c14fb · outbound

This paper cites Semantic Communications: Principles and Challenges.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Semantic Communications: Principles and Challenges

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:32.595840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f812ead4-cff9-4602-a0d3-883aca9eb4e9 · outbound

This paper cites The road towards 6g: A comprehensive survey,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application The road towards 6g: A comprehensive survey,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:38.648490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b2470325-6ac2-460e-9691-d547fdabc170 · outbound

This paper cites Joint source–channel coding: Fundamentals and recent progress in practical designs,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Joint source–channel coding: Fundamentals and recent progress in practical designs,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:38.461727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 70f0473a-3782-4094-8bd4-9d0ee6b28740 · outbound

This paper cites Semantic communication: A survey of its theoretical development,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Semantic communication: A survey of its theoretical development,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:38.168542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 67dfca5c-3a1e-4463-bbfe-c09c22b0fb42 · outbound

This paper cites Deep learning in physical layer: Review on data driven end-to-end communication systems and their enabling semantic applications,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Deep learning in physical layer: Review on data driven end-to-end communication systems and their enabling semantic applications,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:37.912422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ae654e9d-bc12-44fb-b7ac-902d10348fbd · outbound

This paper cites an unresolved cited work.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:19:37.784185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 177147fa-8240-4bf4-bac6-a51c42f94fc4 · outbound

This paper cites Goodfellow, Y.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Goodfellow, Y

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:33.127939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7277c013-cab0-4ba8-86b2-6ce74e167800 · outbound

This paper cites Communication Algorithms via Deep Learning.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Communication Algorithms via Deep Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:33.228743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 919f9d4e-5a8e-48af-9d69-4dd82bcfea73 · outbound

This paper cites Deep joint source- channel coding for wireless image transmission,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Deep joint source- channel coding for wireless image transmission,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:37.582804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5cafc165-326f-433b-8c11-a0ab84901060 · outbound

This paper cites Joint source–channel codes for mimo block- fading channels,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Joint source–channel codes for mimo block- fading channels,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:37.462900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 544eec7e-0843-4262-8ad7-65beaa3cda83 · outbound

This paper cites Diffusion models in vision: A survey,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Diffusion models in vision: A survey,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:33.433340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 309557a3-16ac-4175-914c-2142723e142d · outbound

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

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application High- resolution image synthesis with latent diffusion models,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:33.506096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d62923d5-1c42-4c33-869f-d7c9bd2caf73 · outbound

This paper cites Auto-encoding variational bayes,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Auto-encoding variational bayes,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:33.585519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb60f8f9-669f-4e40-84dc-2071a79a7500 · outbound

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

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Score-Based Generative Modeling through Stochastic Differential Equations

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:33.659607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 950cbbc4-3b37-4709-928e-ad8700e124ee · outbound

This paper cites Simultaneous image-to-zero and zero-to-noise: Diffusion models with analytical image attenuation,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Simultaneous image-to-zero and zero-to-noise: Diffusion models with analytical image attenuation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:37.284425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cb019bc7-5eb8-4469-86c7-559cbe9c481c · outbound

This paper cites Semantic communications: Overview, open issues, and future research directions,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Semantic communications: Overview, open issues, and future research directions,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:37.163245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 279328a2-9b7c-44b8-9c20-be89de07ad02 · outbound

This paper cites Semantics-empowered communications: A tutorial-cum-survey,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Semantics-empowered communications: A tutorial-cum-survey,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:37.026317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4b9ebaaf-a8e1-4890-916f-365516c50700 · outbound

This paper cites A contemporary survey on semantic communications: Theory of mind, generative ai, and deep joint source-channel coding,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application A contemporary survey on semantic communications: Theory of mind, generative ai, and deep joint source-channel coding,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:34.046077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dcc6ce9-be52-40c7-abef-f871236b43d8 · outbound

This paper cites Semantic communication empowered 6G networks: Techniques, applications, and challenges,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Semantic communication empowered 6G networks: Techniques, applications, and challenges,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:36.881112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation abab4463-2880-44b6-9d4a-9624ed4ba432 · outbound

This paper cites Semantic Edge Computing and Semantic Communications in 6G Networks: A Unifying Survey and Research Challenges.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Semantic Edge Computing and Semantic Communications in 6G Networks: A Unifying Survey and Research Challenges

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:34.252436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62b94f4d-08c2-4632-b9bb-965b5d4c754f · outbound

This paper cites A survey on semantic communications in internet of vehicles,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application A survey on semantic communications in internet of vehicles,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:36.761812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a92074f5-56c6-46a2-99a1-062c75ce8ed3 · outbound

This paper cites Modeling and Performance Analysis for Semantic Communications Based on Empirical Results.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Modeling and Performance Analysis for Semantic Communications Based on Empirical Results

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:19:35.672477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6a3691fe-fadc-4d03-9072-768a94bb9c95 · outbound

This paper cites Generative adversarial networks: An overview,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Generative adversarial networks: An overview,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:36.643398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7b729fd9-f4e4-4ba9-91c3-787922393c29 · outbound

This paper cites DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:34.523503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed32fb18-cdb7-4d95-be47-8070567f56d7 · outbound

This paper cites Structured denoising diffusion models in discrete state-spaces,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Structured denoising diffusion models in discrete state-spaces,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:36.532419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e0c08eba-5d53-4e6e-9947-cd08a047d494 · outbound

This paper cites Radiodiff: An effective generative diffusion model for sampling-free dynamic radio map construction,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Radiodiff: An effective generative diffusion model for sampling-free dynamic radio map construction,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:34.725815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 635ba0d7-a11c-4c17-9b23-b645a1385c16 · outbound

This paper cites RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Construction.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application RadioDiff-Inverse: Diffusion Enhanced Bayesian Inverse Estimation for ISAC Radio Map Construction

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:34.792142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 708241d1-cfae-45cd-9896-8da0dbb8c12b · outbound

This paper cites Denoising diffusion probabilistic models,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Denoising diffusion probabilistic models,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:34.826731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e578733-d595-46f2-be6b-3d9417250d1c · outbound

This paper cites Stimulating diffusion model for image denoising via adaptive embedding and ensembling,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Stimulating diffusion model for image denoising via adaptive embedding and ensembling,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:36.421836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f6921131-59f8-40f5-8201-fbfd80e75944 · outbound

This paper cites Decoupled diffusion models: Simultaneous image to zero and zero to noise,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Decoupled diffusion models: Simultaneous image to zero and zero to noise,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:34.977490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53101948-4fbd-4774-ba43-38b8ce2a587e · outbound

This paper cites an unresolved cited work.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:19:36.310644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1c958702-ab79-4886-964f-c4077d4f02dd · outbound

This paper cites Swinjscc: Taming swin transformer for deep joint source-channel coding,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Swinjscc: Taming swin transformer for deep joint source-channel coding,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:36.172576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a5e3a8d5-2e11-47da-82ce-0f049f0f7f57 · outbound

This paper cites Progressive Growing of GANs for Improved Quality, Stability, and Variation.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:35.176689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5876842-8137-4289-9380-fa2da4ae2b8c · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Imagenet: A large-scale hierarchical image database,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:19:36.038435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ee601021-ebd6-4d03-8fbb-9ec6541cf6fd · outbound

This paper cites Image quality assessment: from error visibility to structural similarity,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application Image quality assessment: from error visibility to structural similarity,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:35.384923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec82e68e-f2c6-4b9d-b9e6-f1b1efaea029 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric,.

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application The unreasonable effectiveness of deep features as a perceptual metric,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:35.465967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 926a70cd-b7fd-40cb-806a-d03ab4a1d782 · inbound

Inclusion Arena: An Open Platform for Evaluating Large Foundation Models with Real-World Apps cites this paper.

Inclusion Arena: An Open Platform for Evaluating Large Foundation Models with Real-World Apps Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-05T19:57:12.413788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.