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Paper Citation Record · LEDGER

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research

As of 8 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 2 inbound Pith citation observations for arXiv:2505.19322.

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

pith.paper-citation-record.v1
2505.19322 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:19:28.796741Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T04:50:31.532908Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T10:46:32.493458Z

Reference resolution

22 of 22 outbound references displayed

  • verified exact0
  • verified fuzzy7
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 65f3ad9f-f1a1-48ca-904b-31e86c31d797 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 1

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unresolved
no resolver link, observed 2026-08-07T14:19:25.704355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:25.704355Z digest=sha256:16ac47e3fb89fbb21c78e736177b4086fd7a2b0c0f713b83a436f121d980f4c1

Observation f2d051ce-153d-4f59-ba1c-e26cf295e4e9 · outbound

This paper cites A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 2

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unresolved
no resolver link, observed 2026-08-07T14:19:25.802880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:25.802880Z digest=sha256:a0e86222a7d5315b03a051e44900a39bbc9eab4b52688cba8bdde161fa2d30a0

Observation 64a9ce07-e589-4d09-8557-b6b1f57cd919 · outbound

This paper cites Large generative ai models for telecom: The next big thing?.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research Large generative ai models for telecom: The next big thing?

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:19:31.396216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:19:25.938949Z digest=sha256:8d799836245c2256725a2277540eee3016d600076575e8eaec17a3dfd095f59c

Observation a50b430c-36ad-433f-9a77-d2c0665bf818 · outbound

This paper cites Transformer-empowered 6g intelligent networks: From massive mimo processing to semantic communication,.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research Transformer-empowered 6g intelligent networks: From massive mimo processing to semantic communication,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-07T14:19:31.116486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:19:26.073612Z digest=sha256:65f9675bbfcbca0cc09064b69c617c700829b2e6a99cbc9e641bd6268dce120d

Observation 49341aa4-365f-4df2-9752-02d5f66c5ddc · outbound

This paper cites an unresolved cited work.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:19:30.822321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:19:26.208299Z digest=sha256:d4e8a3ae49583a8cff46aea0212a843496317f1d5be27f3c326d6918682273f2

Observation b19b359c-b93e-4e8f-adf1-598e8937711d · outbound

This paper cites TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T14:19:26.341526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:26.341526Z digest=sha256:f49f1c8bc9a7090b7421a7c2edadae5cb1b993347f4661bd299be7a11d3fcc97

Observation b702c724-4a01-455f-930a-bf246ed7ccd8 · outbound

This paper cites ORAN-Bench-13K: An Open Source Benchmark for Assessing LLMs in Open Radio Access Networks.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research ORAN-Bench-13K: An Open Source Benchmark for Assessing LLMs in Open Radio Access Networks

Reference 7

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unresolved
no resolver link, observed 2026-08-07T14:19:26.462213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:26.462213Z digest=sha256:b3363d3ff8948854b89039c67a2eeb2f9c64d8594941edfe41e9b43e71653bcc

Observation aad1e7df-9e23-4b33-8827-b9c16240849f · outbound

This paper cites TSpec-LLM: An Open-source Dataset for LLM Understanding of 3GPP Specifications.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research TSpec-LLM: An Open-source Dataset for LLM Understanding of 3GPP Specifications

Reference 8

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unresolved
no resolver link, observed 2026-08-07T14:19:26.572094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:26.572094Z digest=sha256:73425603d72b5b27cc1748fcc399c321d94b26d231100b2d490e207008dfd26b

Observation a61e86d9-9501-4639-97a7-af897453c2b2 · outbound

This paper cites SPEC5G: A Dataset for 5G Cellular Network Protocol Analysis.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research SPEC5G: A Dataset for 5G Cellular Network Protocol Analysis

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T14:19:26.714374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:26.714374Z digest=sha256:f79bb88e2acf6d60fcc460072e6050d2136c9a17bdc51b5f550e688db8c4219c

Observation fe350b00-5739-4e19-bba7-2c3cbef1de78 · outbound

This paper cites The Power of Large Language Models for Wireless Communication System Development: A Case Study on FPGA Platforms.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research The Power of Large Language Models for Wireless Communication System Development: A Case Study on FPGA Platforms

Reference 11

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unresolved
no resolver link, observed 2026-08-07T14:19:27.114127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:27.114127Z digest=sha256:596c94ee9a1e01089b15b21664fdae167286122b9d6d7dbf118a35e10870ab99

Observation 07d79430-d080-4940-a419-e1fdf1c60f8e · outbound

This paper cites Unlocking telecom domain knowledge using llms,.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research Unlocking telecom domain knowledge using llms,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:19:30.538564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:19:27.240179Z digest=sha256:f9590c3d38e22e659175f2a5bbab81f14458f544e6b9eab4c313e809548f3959

Observation a30578bd-0d0c-4b90-ad8b-cf9b0542d13a · outbound

This paper cites Large language models for wireless networks: An overview from the prompt engineering perspective,.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research Large language models for wireless networks: An overview from the prompt engineering perspective,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:19:30.226185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:19:27.407030Z digest=sha256:ca51d0df33ea9c0458b21268e2967b570549d44aa46e7f4e80c1eafb4bdbed1c

Observation c8202ca2-17ac-4a64-96fe-9cab2a914322 · outbound

This paper cites MM-LLMs: Recent Advances in MultiModal Large Language Models.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research MM-LLMs: Recent Advances in MultiModal Large Language Models

Reference 14

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unresolved
no resolver link, observed 2026-08-07T14:19:27.561893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:27.561893Z digest=sha256:70058da0b061905e4643728227b1eb4ce54c7f65a2aae3eabe3c3cfb80deeb21

Observation c8b60b73-6ec7-4235-8638-35fd9ca67fbe · outbound

This paper cites How powerful are decoder-only transformer neural models?.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research How powerful are decoder-only transformer neural models?

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:19:29.903980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:19:27.734902Z digest=sha256:cd7d8bfbf1a42db1ff0d4a7f0cbcaf48ecf7f32e68325e6cf6a9d14db1ce1270

Observation c2582210-05d6-4aa0-964a-fa98933e9215 · outbound

This paper cites Mixtral of Experts.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research Mixtral of Experts

Reference 16

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unresolved
no resolver link, observed 2026-08-07T14:19:27.878460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:27.878460Z digest=sha256:b9b3f2727ff635954553b794fa764834b7b0f4953cc3e1fce6661fbabfd737ce

Observation 9f7f6c9a-64a6-4442-964a-16154f2f68c8 · outbound

This paper cites The llama 3 herd of models,.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research The llama 3 herd of models,

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T14:19:28.007647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:28.007647Z digest=sha256:ed83bea78b2d6e59837650c4ab8ffafeb810c98bdc33453d661ef5cb34f4c459

Observation cbd2d11f-fe7f-40fd-b3a8-44bb3c5bb29e · outbound

This paper cites The Faiss library.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research The Faiss library

Reference 18

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unresolved
no resolver link, observed 2026-08-07T14:19:28.178652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:28.178652Z digest=sha256:afe2e2d57c47119c6daf904bf87006a4231eb0dcb7cefedfe4f6a072a73931c9

Observation 875452f1-9969-4d4a-93f0-be0b1ab11f8d · outbound

This paper cites Ragas llm evaluator.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research Ragas llm evaluator

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:19:29.585833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:19:28.295957Z digest=sha256:54a8568cbe0062ce2a466bac7d859231f6d5ab2dafcacba4d66ab4ba4e7bf7f7

Observation cdd034e0-f788-4419-af9e-4563bc3fda9b · outbound

This paper cites Mistral 7B.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research Mistral 7B

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T14:19:28.464906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:28.464906Z digest=sha256:b2c15bdb5b46ed46411aae48e8e3228b57b0cf4175e9af8e202f5526b61dec4e

Observation 9c9f98d6-f823-4956-ba64-f5993b8bf2e8 · outbound

This paper cites Jasper and Stella: distillation of SOTA embedding models.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research Jasper and Stella: distillation of SOTA embedding models

Reference 21

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unresolved
no resolver link, observed 2026-08-07T14:19:28.796741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:28.796741Z digest=sha256:ac25ae836ca2dddea3133087a17a506d67d881bfc2699c57f4f8f19549f9297d

Observation 51d768d3-c6f3-4a32-9333-7554aadb5de9 · outbound

This paper cites Available: https://api.semanticscholar.org/CorpusID: 263830494.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research Available: https://api.semanticscholar.org/CorpusID: 263830494

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:19:29.319919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T14:19:28.649327Z digest=sha256:580cb704f285d4bc251410cc9eb24d0e8409d66a0d5902d650571bb01094fc41

Observation 7eb5c347-f304-4ecb-ac0e-2bbc9c2102c3 · outbound

This paper cites WirelessLLM: Empowering Large Language Models Towards Wireless Intelligence.

NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research WirelessLLM: Empowering Large Language Models Towards Wireless Intelligence

Reference 2024

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unresolved
no resolver link, observed 2026-08-07T14:19:26.997798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:26.997798Z digest=sha256:2d98d32549a79f6adcdc0ef1c898c3d11e73ac8147b6fbd987a72c367ac9a0ba

Pith citing papers

Observation 9e0c0ee8-33bc-423c-b110-a55ebf951fe3 · 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 NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research

Reference 28

Resolution
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no resolver link, observed 2026-08-05T04:50:31.532908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T04:50:31.532908Z digest=sha256:c17e05061d023d8833ddff58f2daf5414a17b7da851dc904b82b99e5078c98ec

Observation 76dfa5a9-5753-4e22-a3a7-98138eac7911 · inbound

Enwar 3.0: An Agentic Multi-Modal LLM Orchestrator for Situation-Aware Beamforming, Blockage Prediction, and Handover Management cites this paper.

Enwar 3.0: An Agentic Multi-Modal LLM Orchestrator for Situation-Aware Beamforming, Blockage Prediction, and Handover Management NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:46:32.497072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T01:56:01.451833Z digest=sha256:1d43889ede09735ccbae7927be6d12a8593776b6bbcdd410bc2452b0ebe5cae5