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Paper Citation Record · LEDGER

Diffusion Model for Multiple Antenna Communications

As of 22 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2502.01841.

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

pith.paper-citation-record.v1
2502.01841 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:20:05.287609Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

13 of 13 outbound references displayed

  • verified exact1
  • verified fuzzy11
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1a2e0569-60d3-474a-8679-2cece82f501a · outbound

This paper cites Near-field communications: A comprehensive survey,.

Diffusion Model for Multiple Antenna Communications Near-field communications: A comprehensive survey,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T14:20:05.505369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-09T14:20:05.235696Z digest=sha256:ed37c3a14bde5f4e63b92cc6e6b96dd2a69ca7632712b1ddcd5522886e0bc57d

Observation c3c03f0b-71b7-46ac-b86d-698317309504 · outbound

This paper cites Enhancing deep reinforcement learning: A tutorial on generative diffusion models in network optimization,.

Diffusion Model for Multiple Antenna Communications Enhancing deep reinforcement learning: A tutorial on generative diffusion models in network optimization,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T14:20:05.491039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-09T14:20:05.239897Z digest=sha256:12444b6603442ca4d4c3c70768485b5727be6272285db4588ac80e78e0ed50a9

Observation ef0c0fc9-64a5-49f4-aeff-1584b86223fe · outbound

This paper cites Generative vs. Discriminative modeling under the lens of uncertainty quantification.

Diffusion Model for Multiple Antenna Communications Generative vs. Discriminative modeling under the lens of uncertainty quantification

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-09T14:20:05.355204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-09T14:20:05.244170Z digest=sha256:36af051590bfd7e3457bd541985b2cf90435acf218ab2e2a23e9157b2919207d

Observation f28819d5-9b31-4d35-8b9b-72ac0cae8b08 · outbound

This paper cites Policy Representation via Diffusion Probability Model for Reinforcement Learning.

Diffusion Model for Multiple Antenna Communications Policy Representation via Diffusion Probability Model for Reinforcement Learning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-09T14:20:05.248487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T14:20:05.248487Z digest=sha256:3d4b709c7aeca8fe5925212ab1d32aa222caa43b990b61a2ec2bfdd89b7a4d90

Observation 888dc7b0-00c6-42fb-8b99-8f30d94aed00 · outbound

This paper cites Generative artificial intelligence for mobile communications: A diffusion model perspective,.

Diffusion Model for Multiple Antenna Communications Generative artificial intelligence for mobile communications: A diffusion model perspective,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T14:20:05.478754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-09T14:20:05.253189Z digest=sha256:919bc4b8de50cc15ac43e1f8b3e523908e25e8ea8081f94a2a976c8ec8d2c250

Observation 7d9a8e3a-90cf-46b7-a350-f677c4d2be36 · outbound

This paper cites Learning-based signal detection for MIMO systems with unknown noise statistics,.

Diffusion Model for Multiple Antenna Communications Learning-based signal detection for MIMO systems with unknown noise statistics,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T14:20:05.466932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-09T14:20:05.258082Z digest=sha256:02058b0919b7e6cb074871fe2ea6a132262c5a81e8cf36a873e5d707df43e37b

Observation 2be8cde4-90ed-4436-ab17-eb029ed61efd · outbound

This paper cites Generative AI for integrated sensing and communication: Insights from the physical layer perspective,.

Diffusion Model for Multiple Antenna Communications Generative AI for integrated sensing and communication: Insights from the physical layer perspective,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T14:20:05.454818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-09T14:20:05.263381Z digest=sha256:49fb0cfe0a9ec4ef8ba4f347ccb852598583fbdd2e8635d09f93481246097673

Observation 1dc6497d-bd18-4dbf-9663-bd7eba4d879a · outbound

This paper cites Denoising diffusion probabilistic models,.

Diffusion Model for Multiple Antenna Communications Denoising diffusion probabilistic models,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T14:20:05.442381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-09T14:20:05.267296Z digest=sha256:de62c59c3ff879c5998c84f1899986688bba456a46df81677d33fee1cc852334

Observation 47795c2a-dfd0-46bc-ab3f-69b4631c5cbd · outbound

This paper cites Learning optimal resource allocations in wireless systems,.

Diffusion Model for Multiple Antenna Communications Learning optimal resource allocations in wireless systems,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T14:20:05.427038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-09T14:20:05.270863Z digest=sha256:c55f9f65614251d99efb82ef481008ddf34b586e53f822a72dc9025233f0e762

Observation 891368c9-2f85-4beb-bde7-220d3acc2357 · outbound

This paper cites Optimizing wireless systems using unsupervised and reinforced-unsupervised deep learning,.

Diffusion Model for Multiple Antenna Communications Optimizing wireless systems using unsupervised and reinforced-unsupervised deep learning,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T14:20:05.414146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-09T14:20:05.274874Z digest=sha256:3e718084577bd6edd02c5feb5ebd58216a715bb5be91e32b439c78509980db78

Observation e4407720-fea3-4d3a-aeb8-68e316f7b44b · outbound

This paper cites Optimal multiuser trans- mit beamforming: A difficult problem with a simple solution structure,.

Diffusion Model for Multiple Antenna Communications Optimal multiuser trans- mit beamforming: A difficult problem with a simple solution structure,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T14:20:05.399910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-09T14:20:05.279244Z digest=sha256:35506a477371c03c544ddcefe6df8712f0e83f2c6bf4bf85ed33e8b0e0b7c35e

Observation 07da5163-4876-4166-8e1d-76744be1f798 · outbound

This paper cites Electromagnetic property sensing based on diffusion model in ISAC system,.

Diffusion Model for Multiple Antenna Communications Electromagnetic property sensing based on diffusion model in ISAC system,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T14:20:05.386584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-09T14:20:05.283502Z digest=sha256:a26784b1ecaf638ea6c39f914aae4908874a9eab0f8b0b3327ed26feba7cbfde

Observation 8f1f8c91-70c8-422c-9e08-71544a761a1e · outbound

This paper cites Multidimensional graph neural networks for wireless communications,.

Diffusion Model for Multiple Antenna Communications Multidimensional graph neural networks for wireless communications,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T14:20:05.373199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-09T14:20:05.287609Z digest=sha256:06a9629bc6b2f5255d49a19e183c7852597451cf7ab3c1c4f252cdab0df344e6

Pith citing papers

No inbound Pith citation observations are available.