Pith. sign in

Paper Citation Record · LEDGER

AI and Deep Learning for Terahertz Ultra-Massive MIMO: From Model-Driven Approaches to Foundation Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.09839.

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

pith.paper-citation-record.v1
2412.09839 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:42:05.159437Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T20:06:10.579029Z

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 a28e4a58-667c-4b5e-b16b-3fe28c9e3b54 · inbound

A look at adversarial attacks on radio waveforms from discrete latent space cites this paper.

A look at adversarial attacks on radio waveforms from discrete latent space AI and Deep Learning for Terahertz Ultra-Massive MIMO: From Model-Driven Approaches to Foundation Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:05.159437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:05.159437Z digest=sha256:e8abdb140bb82602bfb17c8eefe5c5e5869cbdc6698f7a5a3c5f511f73aa1456

Observation 45cc55da-1106-4e44-8797-a1aae533444a · inbound

When AI Meets Terahertz: A Survey on the Symbiosis of Artificial Intelligence and Terahertz Networks cites this paper.

When AI Meets Terahertz: A Survey on the Symbiosis of Artificial Intelligence and Terahertz Networks AI and Deep Learning for Terahertz Ultra-Massive MIMO: From Model-Driven Approaches to Foundation Models

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:06:10.583516Z

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.

source=pdf_text observed=2026-05-08T10:18:50.396732Z digest=sha256:2cd95f8794a9906a595abb03e437f40949b4ef74db641c622424c67b6ecc5f4f