Paper Citation Record · LEDGER

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G

As of 19 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 1 inbound Pith citation observation for arXiv:2506.14288.

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

pith.paper-citation-record.v1
2506.14288 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:22:25.854759Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T20:32:17.658231Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T20:35:02.502384Z

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy9
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 202e76bd-2d9b-4b90-b079-ecae681a354d · outbound

This paper cites A tutorial on fluid antenna system for 6G networks: Encompassing communication theory, optimization methods and hard- ware designs,.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G A tutorial on fluid antenna system for 6G networks: Encompassing communication theory, optimization methods and hard- ware designs,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:23.622922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 244b2286-3950-45bc-bb07-e7769ed55995 · outbound

This paper cites Virtual FAS by learning-based imaginary antennas,.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G Virtual FAS by learning-based imaginary antennas,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:29.168307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eed40649-b0e4-4bdc-b05c-4394a50c6f17 · outbound

This paper cites Fluid antenna system liberating multiuser MIMO for ISAC via deep reinforcement learning,.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G Fluid antenna system liberating multiuser MIMO for ISAC via deep reinforcement learning,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:28.874749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c6ed6b5d-5fa2-4fde-a114-ef1a4a9329c6 · outbound

This paper cites AI-empowered fluid antenna systems: Opportunities, challenges, and future directions,.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G AI-empowered fluid antenna systems: Opportunities, challenges, and future directions,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:28.624909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 50838da0-af10-41f6-bd1a-4e9c44100ed4 · outbound

This paper cites Generative AI Enabled Robust Data Augmentation for Wireless Sensing in ISAC Networks.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G Generative AI Enabled Robust Data Augmentation for Wireless Sensing in ISAC Networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:24.170671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2f06628-0fdb-457d-a867-da6d372b8316 · outbound

This paper cites Generative AI agents with large language model for satellite networks via a mixture of experts transmission,.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G Generative AI agents with large language model for satellite networks via a mixture of experts transmission,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:28.295963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fbedcce2-97a7-4adc-b662-ad56f3781c96 · outbound

This paper cites FAS-LLM: Large Language Model-Based Channel Prediction for OTFS-Enabled Satellite-FAS Links.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G FAS-LLM: Large Language Model-Based Channel Prediction for OTFS-Enabled Satellite-FAS Links

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:24.504827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d76bd04e-48be-4fd1-a9d4-55d9d28af5a5 · outbound

This paper cites Port-LLM: A Port Prediction Method for Fluid Antenna based on Large Language Models.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G Port-LLM: A Port Prediction Method for Fluid Antenna based on Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:24.744753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbd627f5-19dc-49fb-8f63-7d1c1de6ddd7 · outbound

This paper cites Channel knowledge map aided channel prediction with measurements-based evaluation,.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G Channel knowledge map aided channel prediction with measurements-based evaluation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:28.064775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a515bb84-2da3-4549-a36e-0dfdcd90649f · outbound

This paper cites Knowing What Not to Do: Leverage Language Model Insights for Action Space Pruning in Multi-agent Reinforcement Learning.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G Knowing What Not to Do: Leverage Language Model Insights for Action Space Pruning in Multi-agent Reinforcement Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:25.044749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fae5bc5-e8ea-48a1-9e82-7a66ef7d9d82 · outbound

This paper cites A Survey on Multimodal Large Language Models.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G A Survey on Multimodal Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T00:22:25.204974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b3ab284-8eff-409c-bc90-793de91723bf · outbound

This paper cites Benchmarking large language models in retrieval-augmented generation,.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G Benchmarking large language models in retrieval-augmented generation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:27.832121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3ea6e156-97c4-4f59-8b7f-1e7245ef7f9c · outbound

This paper cites Using large language models for hyperparameter optimization,.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G Using large language models for hyperparameter optimization,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:27.554956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 833b4167-e039-4e5e-9ef7-ac693f504493 · outbound

This paper cites Llm4cp: Adapting large language models for channel prediction,.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G Llm4cp: Adapting large language models for channel prediction,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:27.270458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 475545c1-ca7c-4ed3-955e-fd698265ccfc · outbound

This paper cites Reevo: Large language models as hyper-heuristics with reflective evolution,.

Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G Reevo: Large language models as hyper-heuristics with reflective evolution,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:22:26.905262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 12107696-cc6c-4921-9f0e-9f6d97752d07 · inbound

LLM-Enabled Automated Algorithm Design for Multiuser Fluid Antenna Communications cites this paper.

LLM-Enabled Automated Algorithm Design for Multiuser Fluid Antenna Communications Large Language Model Empowered Design of Fluid Antenna Systems: Challenges, Frameworks, and Case Studies for 6G

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-06-30T20:35:02.504202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.