Paper Citation Record · LEDGER

A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites

As of 10 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2502.08757.

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

pith.paper-citation-record.v1
2502.08757 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:50:34.821013Z

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

11 of 11 outbound references displayed

verified exact0
verified fuzzy9
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3fb62351-6fea-41b9-9047-412c3a5f293d · outbound

This paper cites Dynamic spectrum management: Complexity and duality,.

A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites Dynamic spectrum management: Complexity and duality,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:50:35.020235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c404e06c-e4a8-47e6-9032-6d4189af82f5 · outbound

This paper cites An Iteratively Weighted MMSE Approach to Distributed Sum-Utility Maximization for a MIMO Interfering Broadcast Channel,.

A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites An Iteratively Weighted MMSE Approach to Distributed Sum-Utility Maximization for a MIMO Interfering Broadcast Channel,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:50:35.003740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1074ca4d-36cd-48c0-a5b5-24737b8c1051 · outbound

This paper cites Unsupervised deep learning for massive MIMO hybrid beamforming,.

A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites Unsupervised deep learning for massive MIMO hybrid beamforming,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:50:34.985663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6255d368-34b9-401c-a2a0-b41555dc3b58 · outbound

This paper cites Unfolding WMMSE using graph neural networks for efficient power allocation,.

A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites Unfolding WMMSE using graph neural networks for efficient power allocation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:50:34.969316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0fda5b7c-2385-4638-975a-af1276836105 · outbound

This paper cites A learning- aided flexible gradient descent approach to MISO beamforming,.

A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites A learning- aided flexible gradient descent approach to MISO beamforming,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:50:34.952923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cf0959b0-50b5-4eaf-bab3-f89250fa2ad4 · outbound

This paper cites A deep learning framework for optimization of MISO downlink beam- forming,.

A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites A deep learning framework for optimization of MISO downlink beam- forming,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:50:34.935961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fbd8422b-d3f8-4b6b-a065-b6fe576555e2 · outbound

This paper cites Downlink beamforming prediction in MISO system using meta learning and unsupervised learning,.

A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites Downlink beamforming prediction in MISO system using meta learning and unsupervised learning,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:50:34.919017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1bc2c849-22ed-4773-8b27-ddb6f42e6af1 · outbound

This paper cites Teacher-Student Architecture for Knowledge Distillation: A Survey.

A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites Teacher-Student Architecture for Knowledge Distillation: A Survey

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T23:50:34.805677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6c6ad6a-e029-4a35-9b03-7d0033f6fd5a · outbound

This paper cites Planet dump retrieved from https://planet.osm.org ,.

A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites Planet dump retrieved from https://planet.osm.org ,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T23:50:34.810919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d91e7b25-1ab6-4119-99e9-9adaa52cf319 · outbound

This paper cites SAGE- HB: Swift adaptation and generalization in massive MIMO hybrid beam- forming,.

A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites SAGE- HB: Swift adaptation and generalization in massive MIMO hybrid beam- forming,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:50:34.892182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5e4e4c29-d982-4ba6-8949-d9a186202c94 · outbound

This paper cites Precoding and power optimization in cell-free massive MIMO systems,.

A Low-Complexity Plug-and-Play Deep Learning Model for Massive MIMO Precoding Across Sites Precoding and power optimization in cell-free massive MIMO systems,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T23:50:34.875257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.