Pith. sign in

Paper Citation Record · LEDGER

A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2505.03556.

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

pith.paper-citation-record.v1
2505.03556 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:13:46.405416Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T11:28:14.669989Z

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 803fefbd-00fa-4a79-9cce-debcb9b9ae8d · inbound

From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications cites this paper.

From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T13:13:46.405416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:13:46.405416Z digest=sha256:3af0546977801fa5efb7f48c70ac122b39d067cc9968663611ba512d7f3f019f

Observation 9cdbcd9b-8d35-4fcf-a0bf-a5a6665b0182 · inbound

Graph Representation-based Model Poisoning on Federated Large Language Models cites this paper.

Graph Representation-based Model Poisoning on Federated Large Language Models A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T20:51:11.399841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:51:11.399841Z digest=sha256:ccd027a082de4cae11cf1af862c730861a25500f1a35c540501ba4f7fc535bef

Observation 291e62f1-0307-40d3-9588-ab07fd766a1f · inbound

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

Towards channel foundation models (CFMs): Motivations, methodologies and opportunities A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T16:24:45.460974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:24:45.460974Z digest=sha256:f67dbdee760eff100cb08e2d8056749cf8fdf36fbf9ceda2cfb7e071071a8863

Observation 71c218e5-dd37-4eb6-a07b-ac7ad99992c5 · inbound

ADEPTS: A Capability Framework for Human-Centered Agent Design cites this paper.

ADEPTS: A Capability Framework for Human-Centered Agent Design A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T16:11:47.830073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:11:47.830073Z digest=sha256:61027338ce601fa792f9aaae723dc08e6969dd2455064d7ad9d4e7c227b8815e

Observation 827365ab-5bc0-406b-87a9-fc1af5d30741 · inbound

Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges cites this paper.

Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

Reference 164

Resolution
unresolved
no resolver link, observed 2026-08-05T21:02:04.784087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:02:04.784087Z digest=sha256:94e3ffb0c4be56e81250f929ce827beeb87db2844f024f14791be1f0cb106c5b

Observation 281e3dfc-508c-4a28-a46a-39a57d0667d6 · inbound

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial cites this paper.

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T04:50:31.511788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T04:50:31.511788Z digest=sha256:b53e62d5d96819fa47d89876c0751678300fd1a4b25847387a02cfed86bf3fe4

Observation 64a89c88-9300-4a47-942f-4de60da8c2c1 · inbound

Modular PE-Structured Learning for Cross-Task Wireless Communications cites this paper.

Modular PE-Structured Learning for Cross-Task Wireless Communications A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-04T20:27:46.527614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:27:46.527614Z digest=sha256:849f2610dc945196d66756005dc082cf514de208131b25a1ed10fbf9adec8569

Observation 701d5d19-6cd8-49f0-a7d1-31abbaa1d50f · inbound

AI Reasoning for Wireless Communications and Networking: A Survey and Perspectives cites this paper.

AI Reasoning for Wireless Communications and Networking: A Survey and Perspectives A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

Reference 108

Resolution
unresolved
no resolver link, observed 2026-08-04T19:34:31.202544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:34:31.202544Z digest=sha256:1156193b5965f28811daeeae5994cbed21047be9c48044d2154e73e4ddb78062

Observation fa88ecad-d463-4ec3-aee3-0bc4526ef300 · inbound

Tempus: A Temporally Scalable Resource-Invariant GEMM Streaming Framework for Versal AI Edge cites this paper.

Tempus: A Temporally Scalable Resource-Invariant GEMM Streaming Framework for Versal AI Edge A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:51:41.385038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-09T19:09:51.273409Z digest=sha256:23538ba8be055a7bea4886c341477812847b1fae19ac10672323717e543699a4

Observation bc91a0b7-6de7-4e94-9325-524e2c77c6e6 · inbound

TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications? cites this paper.

TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications? A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-20T11:28:14.671748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T11:23:34.256279Z digest=sha256:771d3f87621242b51747a83b03bd4ee27ec4c9554edace021f0520880ed904de