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Paper Citation Record · LEDGER

Building 6G Radio Foundation Models with Transformer Architectures

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2411.09996.

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

pith.paper-citation-record.v1
2411.09996 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:56:47.010616Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T16:24:49.831314Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 7a2a55d3-658d-453e-8b70-85cd189e3b4f · inbound

WirelessGPT: A Generative Pre-trained Multi-task Learning Framework for Wireless Communication cites this paper.

WirelessGPT: A Generative Pre-trained Multi-task Learning Framework for Wireless Communication Building 6G Radio Foundation Models with Transformer Architectures

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-08T18:56:47.010616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:56:47.010616Z digest=sha256:ad75b806525bd4d72e3930d10d77ab680f141f064cb2778dbc199bfac2b68096

Observation a917e72e-8a77-4bee-be3d-c862106feec8 · inbound

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G cites this paper.

IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G Building 6G Radio Foundation Models with Transformer Architectures

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T05:56:03.157952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:56:03.157952Z digest=sha256:fd5ed2672e967e6331b56b1ae93e07ef45daf0bac6a4566554f74c5b403e069f

Observation 0dadf8b1-e667-4fa4-a3a9-f0abf68dc1b9 · inbound

Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration cites this paper.

Foundation Model Empowered Synesthesia of Machines (SoM): AI-native Intelligent Multi-Modal Sensing-Communication Integration Building 6G Radio Foundation Models with Transformer Architectures

Reference 108

Resolution
unresolved
no resolver link, observed 2026-08-07T05:33:55.822461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:33:55.822461Z digest=sha256:0ba67cf930865cedd6a33c787f0f2d0bf5ef5e9d5f1fd15f735dd1d7ee28d9b4

Observation 3b145391-bfc5-41b3-a39f-d07a38c2c3ee · inbound

Towards channel foundation models (CFMs): Motivations, methodologies and opportunities cites this paper.

Towards channel foundation models (CFMs): Motivations, methodologies and opportunities Building 6G Radio Foundation Models with Transformer Architectures

Reference 62

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:24:49.834562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T16:24:47.133972Z digest=sha256:cb3e37abc13b78f5cfdd90c78fdbb60ac3e1095d3f79a7f12d54a13041453801

Observation 5bb132ac-fe50-4081-abc5-0a169463cace · inbound

Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications cites this paper.

Radio-FM: A Foundation Model for Radio Signal Representation Learning and Its Applications Building 6G Radio Foundation Models with Transformer Architectures

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T23:29:03.850180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:29:03.850180Z digest=sha256:ab7806491b26f51b00e1b82f4b8a7755918ebc6761d77be4c28edf180c988c4e