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Paper Citation Record · LEDGER

LLM4CP: Adapting Large Language Models for Channel Prediction

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.14440.

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

pith.paper-citation-record.v1
2406.14440 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:25:15.224312Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T21:07:46.953187Z

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 1e2c3c68-aeca-4acb-8985-cdf5d7229305 · inbound

Large Models Enabled Ubiquitous Wireless Sensing cites this paper.

Large Models Enabled Ubiquitous Wireless Sensing LLM4CP: Adapting Large Language Models for Channel Prediction

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-12T11:25:15.224312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:25:15.224312Z digest=sha256:9b1c747eacc44973071b51b999b32f490546e8dde390e23b20e8b1bca9c90921

Observation f5af658a-c190-486b-9eaf-a99e802df7a8 · inbound

Towards Wireless Native Big AI Model: The Mission and Approach Differ From Large Language Model cites this paper.

Towards Wireless Native Big AI Model: The Mission and Approach Differ From Large Language Model LLM4CP: Adapting Large Language Models for Channel Prediction

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-11T17:25:31.609621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T17:25:31.609621Z digest=sha256:e0c596630d15f3beb3fc7548b705cf51b6b40d585452bdb62a66190fd4aa4cb5

Observation b7b7eb27-7cb7-4b71-8660-acd61a1748b6 · inbound

Against the Monolithic Wireless World Model: Why NextG Needs Composable and Agentic Intelligence cites this paper.

Against the Monolithic Wireless World Model: Why NextG Needs Composable and Agentic Intelligence LLM4CP: Adapting Large Language Models for Channel Prediction

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-19T21:07:46.954848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-19T21:07:40.256977Z digest=sha256:072ca961deb70e1f4d7b208b77d18c6dd761a5bdd08c950b5f8df5719bf34353