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Paper Citation Record · LEDGER

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN

As of 15 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 4 inbound Pith citation observations for arXiv:2507.21696.

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

pith.paper-citation-record.v1
2507.21696 v4

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:30:39.990628Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:20:59.139146Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T01:23:49.505105Z

Reference resolution

29 of 29 outbound references displayed

  • verified exact1
  • verified fuzzy19
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f391563b-82f7-4994-afe1-b5c2dc74ac18 · outbound

This paper cites Transition technologies towards 6g networks.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Transition technologies towards 6g networks

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-06T12:30:40.492585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.917694Z digest=sha256:c0ab5514238b9913b7135137fd2197c8bef8e4a0ab9ceb3df72e3ee1bea55a92

Observation e42e854c-f8b1-47a2-b805-ff8d2d514ca3 · outbound

This paper cites Oran-map: A hybrid approach to mobility-aware power optimisation in open radio access networks (oran).

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Oran-map: A hybrid approach to mobility-aware power optimisation in open radio access networks (oran)

Reference 2

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raw_fallback, observed 2026-08-06T12:30:40.485539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.920853Z digest=sha256:f3e0098fbcc1cc941e3ee7098145895a1888bb28696b53b01f3e1ebb4bdc070a

Observation 238e33b7-016d-403d-93a2-f0447d1e88f2 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 3

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T12:30:39.923932Z digest=sha256:930a112c93c40731fcac013e27711a4d2cdf60735a2e15e20a6b0c754f6070b1

Observation ee6a414e-d480-4cef-86a3-49f1a13b1e2a · outbound

This paper cites Llm-driven agentic ai approach to enhanced o-ran resilience in next-generation networks, May 2025.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Llm-driven agentic ai approach to enhanced o-ran resilience in next-generation networks, May 2025

Reference 4

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raw_fallback, observed 2026-08-06T12:30:40.478248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.926854Z digest=sha256:a103cde3522f2a7f2360beee3f34f1b62f4bbfdd06223d5c4a22188784722ffb

Observation 5caca143-129c-48e6-bde7-b0835de67397 · outbound

This paper cites PersonaGym: Evaluating Persona Agents and LLMs.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN PersonaGym: Evaluating Persona Agents and LLMs

Reference 5

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no resolver link, observed 2026-08-06T12:30:39.929548Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T12:30:39.929548Z digest=sha256:9cd2a16ab37a992d7e72efaff00e5a97abbc4e5af6817a974d0126c52f765df9

Observation 3c14a9fa-c4c3-4ffe-8301-c7cbd3ed3198 · outbound

This paper cites ChatHaruhi: Reviving Anime Character in Reality via Large Language Model.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN ChatHaruhi: Reviving Anime Character in Reality via Large Language Model

Reference 6

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T12:30:39.932289Z digest=sha256:49b9c1a82346a284fb6283b7e969f88c9e738f9f846b6231942c994b2b2f1cc8

Observation 94ae557a-b676-4afa-8b18-7ba81ddfa065 · outbound

This paper cites Better Zero-Shot Reasoning with Role-Play Prompting.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Better Zero-Shot Reasoning with Role-Play Prompting

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:30:39.935329Z digest=sha256:2ca8a0fc309a97659d4a6e7d570e25c1ede5d1145e1ced1272f3184023a32c88

Observation 23fe2058-792e-4e80-bdcc-0e369a37b1a6 · outbound

This paper cites Softbank corp.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Softbank corp

Reference 8

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raw_fallback, observed 2026-08-06T12:30:40.470457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.938030Z digest=sha256:71d3f85341ebec216523583243a78d3d2695433cf9625fc03df3eeba43b10bb8

Observation 96a7546e-86be-4292-b453-a3c0d6de210e · outbound

This paper cites Nvidia ai aerial launches to optimize wireless networks, deliver new generative ai experiences on one platform.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Nvidia ai aerial launches to optimize wireless networks, deliver new generative ai experiences on one platform

Reference 9

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raw_fallback, observed 2026-08-06T12:30:40.463338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.940588Z digest=sha256:b554d0828712f475dc86c5aedf6f543752283ccb36911b36d873bd28eb28d6bb

Observation 092198e0-1352-44d9-8433-070820056031 · outbound

This paper cites Evaluating generative ai for telecom.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Evaluating generative ai for telecom

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.943007Z digest=sha256:ab0e1ec7f1b699d1a7101c9a0a421c8e034469ca95f96b85f2e4e73fb8f6c899

Observation 64ff1af3-7297-4439-9910-8c7214c314f1 · outbound

This paper cites Deploy ai-ran at cell sites with nvidia arc-compact.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Deploy ai-ran at cell sites with nvidia arc-compact

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.945392Z digest=sha256:bf218528784a5816e4754d287053e4eb2cfa6fbe95f1bee076da2c5487f1ffce

Observation 81d871da-0d45-4dd6-b3d4-418e0a4c11e4 · outbound

This paper cites Joint admission control and resource provisioning for urllc traffic in o-ran: A constrained multi- agent reinforcement learning approach, May 2025.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Joint admission control and resource provisioning for urllc traffic in o-ran: A constrained multi- agent reinforcement learning approach, May 2025

Reference 12

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raw_fallback, observed 2026-08-06T12:30:40.441782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.947687Z digest=sha256:f588af15116c8365657b225f43260d9d814e16a7b6fe41dee86eb752eceb0d8f

Observation 08c97512-c742-47f2-9c30-88980a06ef6f · outbound

This paper cites Explainable ai in 6g o-ran: A tutorial and survey on architecture, use cases, challenges, and future research.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Explainable ai in 6g o-ran: A tutorial and survey on architecture, use cases, challenges, and future research

Reference 13

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raw_fallback, observed 2026-08-06T12:30:40.434277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.950403Z digest=sha256:c520012a0675441d9f93466552504ef2239912c504d169b58c10b661cf6bd4ff

Observation 54a45e1e-c13c-43dd-86f1-1808bf9e6e5b · outbound

This paper cites FedORA: Resource Allocation for Federated Learning in ORAN using Radio Intelligent Controllers.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN FedORA: Resource Allocation for Federated Learning in ORAN using Radio Intelligent Controllers

Reference 14

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local_arxiv, observed 2026-08-06T12:30:40.317976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.952676Z digest=sha256:9ef5e75b8fb1f29e2245c8633b908d944ff19ac8309993f0649b8427ccd5e475

Observation 93515012-64ed-4494-940a-046c27959dbc · outbound

This paper cites Alympics: Llm agents meet game theory.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Alympics: Llm agents meet game theory

Reference 15

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raw_fallback, observed 2026-08-06T12:30:40.426344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.955389Z digest=sha256:1039f851682e7d81634aa0987e4c31b46b47d0b72b3d5f809b2fdc790049dc7e

Observation bcf4d2af-5ec5-44a0-8e26-7743d8ec65f3 · outbound

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

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge

Reference 16

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T12:30:39.957816Z digest=sha256:6730ac1d75c70dd3d1cf96b7ad4dff8416d1f15a572910899d7736be64696cac

Observation c237ae26-c389-4a95-863a-b0cd88442a78 · outbound

This paper cites Advanced architectures integrated with agentic ai for next-generation wireless networks.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Advanced architectures integrated with agentic ai for next-generation wireless networks

Reference 17

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source=pdf_text observed=2026-08-06T12:30:39.960572Z digest=sha256:c000a1a014ec0203e8a0022a39dc413aab34625a8e3bc3e6a03c285077a12d20

Observation 31566e6e-be2c-49fb-9631-feb76d533484 · outbound

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

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN The Power of Large Language Models for Wireless Communication System Development: A Case Study on FPGA Platforms

Reference 18

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source=pdf_text observed=2026-08-06T12:30:39.963291Z digest=sha256:9e2b9aae1a9debbca02390bb494d8253d858bf5a6bcff6f027c2100af6513226

Observation 9561de62-4b4c-454a-8a7c-dfca391392c1 · outbound

This paper cites Llm-based policy generation for intent-based management of applications.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Llm-based policy generation for intent-based management of applications

Reference 19

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raw_fallback, observed 2026-08-06T12:30:40.419127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.965892Z digest=sha256:05ef84639482ddbb89331cee1dd21a1390a48632dd8b0364319fcaddb0cdd957

Observation 098e7ec8-9da6-4c7d-816d-a71c958df219 · outbound

This paper cites What do llms need to synthesize correct router configurations? In Proceedings of the 22nd ACM Workshop on Hot Topics in Networks , pages 189–195, 2023.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN What do llms need to synthesize correct router configurations? In Proceedings of the 22nd ACM Workshop on Hot Topics in Networks , pages 189–195, 2023

Reference 20

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raw_fallback, observed 2026-08-06T12:30:40.411654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.968212Z digest=sha256:41cd53c17d579011ee5382b728df84e54515ae694d78be00c1127644e1ed280b

Observation ae791450-971f-480e-b54d-f3088c3ae928 · outbound

This paper cites Toward reproducing network research results using large language models.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Toward reproducing network research results using large language models

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.970927Z digest=sha256:260775ae2a0396399f161b1c7ca4cb7747be4fbf99b79edbfd7c8054ebc108bd

Observation 467b3dea-1ad4-46a1-87c6-9297f82036ab · outbound

This paper cites Wireless Multi-Agent Generative AI: From Connected Intelligence to Collective Intelligence.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Wireless Multi-Agent Generative AI: From Connected Intelligence to Collective Intelligence

Reference 22

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no resolver link, observed 2026-08-06T12:30:39.973326Z

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source=pdf_text observed=2026-08-06T12:30:39.973326Z digest=sha256:d9e7f2b902969d2efbad8c6281b7bf89a6bfb459f3c40425c63b60bde1d641e3

Observation 61a75cbb-ee2a-4deb-9485-ccdbb7e86547 · outbound

This paper cites Edgefm: Leveraging foundation model for open-set learning on the edge.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Edgefm: Leveraging foundation model for open-set learning on the edge

Reference 23

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raw_fallback, observed 2026-08-06T12:30:40.396267Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.976006Z digest=sha256:1710c0d5d171d3814ac3532fb530b7a8e82f01ffb09c77a98cfd30dd9fd904b2

Observation aa6cdb45-454b-4820-a9c3-9def87f41ace · outbound

This paper cites Et-bert: A contextualized datagram representation with pre-training transformers for encrypted traffic classification.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Et-bert: A contextualized datagram representation with pre-training transformers for encrypted traffic classification

Reference 24

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.978374Z digest=sha256:3cffec6588e4e1a4238e29228174bdfe77e5f3199fdbf443db04280190cc5f58

Observation 158fe600-ef6b-423d-b6c2-3bc5a8a134f2 · outbound

This paper cites Reward Design with Language Models.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Reward Design with Language Models

Reference 25

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source=pdf_text observed=2026-08-06T12:30:39.980782Z digest=sha256:f3e78aa7fd0a9e8aff72de718bd764bb15df5fa27c770e07bdcac1f5d01ce9b3

Observation 937dce6a-a013-4647-9c9a-bcadbe7fe286 · outbound

This paper cites Diagnosing infeasible optimization problems using large language models.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Diagnosing infeasible optimization problems using large language models

Reference 26

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raw_fallback, observed 2026-08-06T12:30:40.380056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.983325Z digest=sha256:4db018f22452d9721f3fdfe076ef4a29e7e7abe77be73872f4dca356aac06522

Observation 1b8ae0db-3548-42da-bda2-7804bcd63136 · outbound

This paper cites Large language models empowered autonomous edge ai for connected intelligence.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Large language models empowered autonomous edge ai for connected intelligence

Reference 27

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raw_fallback, observed 2026-08-06T12:30:40.372184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.985637Z digest=sha256:5b39e3899e5ef2ff62f5eb3c33e01e1852f2bbf49b6901728ea48e0d9c338498

Observation 18a097ec-9a91-439d-a7e9-4787d6974554 · outbound

This paper cites Parameter-efficient fine-tuning of large-scale pre-trained language models.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Parameter-efficient fine-tuning of large-scale pre-trained language models

Reference 28

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raw_fallback, observed 2026-08-06T12:30:40.364257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.988019Z digest=sha256:8360e25522b92aba524b960a28ada380ede097f82d83ca34c79a98f42eaf0142

Observation f586b3be-fe30-45e3-a597-eae6beaad537 · outbound

This paper cites Mobile- llama: Instruction fine-tuning open-source llm for network analysis in 5g networks.

Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN Mobile- llama: Instruction fine-tuning open-source llm for network analysis in 5g networks

Reference 29

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raw_fallback, observed 2026-08-06T12:30:40.356342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T12:30:39.990628Z digest=sha256:0d836c1e89034404ddbaf4533ca2d26dfbc656dbaf07c63a6a6ff2bcc19c881d

Pith citing papers

Observation 163f1d8d-fc60-4952-932d-e9b1d469ef6d · inbound

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions cites this paper.

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN

Reference 46

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source=pdf_text observed=2026-08-05T16:20:59.139146Z digest=sha256:c555f8aed1e000728eb649d2ec0b7e1d95a3de08bb4d9ad5f033f62fb535b407

Observation 521ce2b1-9303-49b0-b777-fc26bcce037e · inbound

Agentic AI for 6G: A New Paradigm for Autonomous RAN Security Compliance cites this paper.

Agentic AI for 6G: A New Paradigm for Autonomous RAN Security Compliance Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN

Reference 10

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arxiv_id, observed 2026-05-16T22:43:37.802322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-16T22:43:20.760265Z digest=sha256:3fe82ce10d557a6992fd1f36510f344020b6abe0fafa163a72faa960ac068d1c

Observation 68f9dfa0-dc1f-4a65-bbdf-02639badb5df · inbound

Reflection-Driven Self-Optimization 6G Agentic AI RAN via Simulation-in-the-Loop Workflows cites this paper.

Reflection-Driven Self-Optimization 6G Agentic AI RAN via Simulation-in-the-Loop Workflows Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN

Reference 13

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arxiv_id, observed 2026-05-17T01:23:49.507787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-17T01:21:33.692839Z digest=sha256:2d76fc32d52283292aac58113ab713b155297b21b4091b533a8db5e91c0b4718

Observation 8fb3a77f-f4cc-42c1-8d5a-f834bbbb8c8f · inbound

Cost and Accuracy of Long-Term Memory in Distributed Multi-Agent Systems Based on Large Language Models cites this paper.

Cost and Accuracy of Long-Term Memory in Distributed Multi-Agent Systems Based on Large Language Models Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:01:43.536920Z digest=sha256:416bea43eb57cc86c3c3a3a674d50db1740ad2e609c10dd23f8c5069cf194d4b