Paper Citation Record · LEDGER

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS)

As of 10 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 8 inbound Pith citation observations for arXiv:2502.01438.

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

pith.paper-citation-record.v1
2502.01438 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:23:31.431185Z

measured 21 of 21 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:33:41.615155Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T13:18:13.186753Z

Reference resolution

13 of 13 outbound references displayed

verified exact0
verified fuzzy8
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 03f1db4d-c3fd-4f0a-b8f1-a35ad02295a4 · outbound

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

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) Near-field communications: A comprehensive survey,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:23:31.618619Z

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 eb412c5d-3e0f-4420-a9ff-e62a2cec4c5f · outbound

This paper cites Flexible-Antenna Systems: A Pinching-Antenna Perspective.

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) Flexible-Antenna Systems: A Pinching-Antenna Perspective

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-09T15:23:31.139480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 343b272b-95c4-47e3-a5db-46128a5e9c38 · outbound

This paper cites Array Gain for Pinching-Antenna Systems (PASS).

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) Array Gain for Pinching-Antenna Systems (PASS)

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T15:23:31.142578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8463939-f706-4240-8b64-a837f2c6824c · outbound

This paper cites Antenna Activation for NOMA Assisted Pinching-Antenna Systems.

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) Antenna Activation for NOMA Assisted Pinching-Antenna Systems

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-09T15:23:31.146120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35b52d1d-ad06-4872-9505-43188a8ce15e · outbound

This paper cites Pinching-Antenna Systems (PASS): Architecture Designs, Opportunities, and Outlook.

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) Pinching-Antenna Systems (PASS): Architecture Designs, Opportunities, and Outlook

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T15:23:31.149756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d9c5ddf-ea76-4142-a0f7-b7f7ab52fd8e · outbound

This paper cites Learning to optimize: training deep neural networks for interference management,.

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) Learning to optimize: training deep neural networks for interference management,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:23:31.610634Z

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 e51aa50e-4de3-41de-9e71-7ff118997eb5 · outbound

This paper cites ENGNN: A general edge- update empowered GNN architecture for radio resource management in wireless networks,.

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) ENGNN: A general edge- update empowered GNN architecture for radio resource management in wireless networks,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:23:31.601500Z

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 855a85fe-e2ef-4e00-90d3-d9e4565da185 · outbound

This paper cites A graph neural network learning approach to optimize RIS-assisted federated learning,.

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) A graph neural network learning approach to optimize RIS-assisted federated learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:23:31.592254Z

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 f858ffce-d565-40d5-90c1-601c395bdedb · outbound

This paper cites Recursive GNNs for learning precoding policies with size-generalizability,.

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) Recursive GNNs for learning precoding policies with size-generalizability,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:23:31.582782Z

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 81c68204-439b-4747-a081-566951cc055b · outbound

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

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) Multidimensional graph neural networks for wireless communications,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:23:31.573684Z

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 6856216f-73c3-45f1-935b-0044b9442341 · outbound

This paper cites Learning to reflect and to beamform for intelligent reflecting surface with implicit channel estimation,.

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) Learning to reflect and to beamform for intelligent reflecting surface with implicit channel estimation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:23:31.564814Z

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 27888b9a-4ebf-470a-b307-b95855da0cdb · outbound

This paper cites Graph neural network aided power control in partially connected cell-free massive MIMO,.

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) Graph neural network aided power control in partially connected cell-free massive MIMO,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:23:31.555381Z

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 79a61646-c89e-4e16-b75b-c0a6ee5c1203 · outbound

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

GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS) Optimal multiuser trans- mit beamforming: A difficult problem with a simple solution structure,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T15:23:31.431185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 77267eb2-21d4-4adc-9a98-cf7973610c84 · inbound

Modeling and Beamforming Optimization for Pinching-Antenna Systems cites this paper.

Modeling and Beamforming Optimization for Pinching-Antenna Systems GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS)

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T17:33:41.615155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 735055dc-1371-40ee-96fc-4da41ad6610e · inbound

Exploiting Pinching-Antenna Systems in Multicast Communications cites this paper.

Exploiting Pinching-Antenna Systems in Multicast Communications GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS)

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T12:10:28.912880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0aa6f75-9b49-48f6-958b-b21b547d981f · inbound

A Gradient Meta-Learning Joint Optimization for Beamforming and Antenna Position in Pinching-Antenna Systems cites this paper.

A Gradient Meta-Learning Joint Optimization for Beamforming and Antenna Position in Pinching-Antenna Systems GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS)

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T00:51:21.749220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9428e94-3a96-4b17-8f69-6ad4497858b3 · inbound

Multigroup Multicast Design for Pinching-Antenna Systems: Waveguide-Division or Waveguide-Multiplexing? cites this paper.

Multigroup Multicast Design for Pinching-Antenna Systems: Waveguide-Division or Waveguide-Multiplexing? GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS)

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T23:54:24.828521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e7aed76-5132-41cd-8361-2d781b9bd912 · inbound

Deep Learning Optimization of Two-State Pinching Antennas Systems cites this paper.

Deep Learning Optimization of Two-State Pinching Antennas Systems GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS)

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T19:14:02.190124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc23e6af-4e37-4530-8510-b3d07ada065b · inbound

Pinching Antenna Systems (PASS): Enabling Reconfigurable and Controllable Wireless Channels -- A Comprehensive Survey cites this paper.

Pinching Antenna Systems (PASS): Enabling Reconfigurable and Controllable Wireless Channels -- A Comprehensive Survey GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS)

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:40:50.403763Z

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 18d59f8b-3e08-45a8-a870-4ac2e6e53f70 · inbound

Spectral- and Energy-efficient Multi-BS Multi-RIS Pinching-antenna Systems: A GNN-based Approach cites this paper.

Spectral- and Energy-efficient Multi-BS Multi-RIS Pinching-antenna Systems: A GNN-based Approach GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS)

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:06:06.677284Z

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 6788fa5a-0066-424c-9271-47f406feec20 · inbound

Reconfigurable Antennas for Next-generation Mobile Communication Networks: A Comprehensive Survey and Tutorial cites this paper.

Reconfigurable Antennas for Next-generation Mobile Communication Networks: A Comprehensive Survey and Tutorial GPASS: Deep Learning for Beamforming in Pinching-Antenna Systems (PASS)

Reference 189

Resolution: verified exact; arxiv_id, observed 2026-07-03T13:18:13.188306Z

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.