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Paper Citation Record · LEDGER

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

As of 9 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.917694Z digest=sha256:c68ca2f7b250be3b1273ee89eaf6b604adf234899696fb3786b0b2f50612c45e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.920853Z digest=sha256:ee89fe5eac854cc6af93015a9450acb7cb0658c6e02ef41a7dbf7bab351e0477

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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no resolver link, observed 2026-08-06T12:30:39.923932Z

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source=pdf_text observed=2026-08-06T12:30:39.923932Z digest=sha256:9f307c0ecb29351843403baa3037ef6bd285a84a8388572b7368f98a0790c1c0

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.926854Z digest=sha256:f4b9372e672fe307606b0dea443570954232ec708ca57d037b2d0c0b9a8a8b70

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:b9ef326bcb6127edc3d04ada981de2bca2bb4c2888d228b8767499b76484f667

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=sha256:544319ba47b62a7b94e101781d34cbe7be09803ff395d3b3fdb5ee006d70bd73

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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source=pdf_text observed=2026-08-06T12:30:39.935329Z digest=sha256:dfc90814f8674a85563526e61032a3943fc7e3866f16f3343b62c6e08815e8f9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.938030Z digest=sha256:a14374e9a949fc6acc84389a54f2e3baad8aa68bf8912a7461cf9499fbec9f80

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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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=2026-08-06T12:30:39.940588Z digest=sha256:10730fa088349a7760d2143017648a7327323742bd6f6b8b15d9e505201f928e

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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raw_fallback, observed 2026-08-06T12:30:40.455925Z

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=2026-08-06T12:30:39.943007Z digest=sha256:794368aaa0f8669758196d489cd1ab4d5bb31107151c1783c2e4e554a8950a73

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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raw_fallback, observed 2026-08-06T12:30:40.448819Z

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=2026-08-06T12:30:39.945392Z digest=sha256:47d1868de53846227bf2d328afd9d56d065dcf0d1f6e45ddd263db4e264cd9b1

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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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=2026-08-06T12:30:39.947687Z digest=sha256:d47529f5b525816813bba519589b25d8489801fb95b242f43d1c2ab079e5b2da

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.950403Z digest=sha256:378f1793021081ff4d0c82f1659e368ae434a4fdb4564961d9551e6081eeb9eb

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.952676Z digest=sha256:acdf5f547ab292788f9b6382cb1634f20dab68aa05f81bd4f31a46f1ebe5553e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.955389Z digest=sha256:b14c947b5c21a704c7167493584e7f037237b78e0e227222e969baffe711053c

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=sha256:28900da788534b55f4f919dd5039d56a6cf3ab5996407282be51e8d660161273

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:acee5185a22bf57358df3176475c372ae37623bddc714b53bedd445a49ad676e

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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no resolver link, observed 2026-08-06T12:30:39.963291Z

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source=pdf_text observed=2026-08-06T12:30:39.963291Z digest=sha256:30d3f9fcff51c8e715d2a3265dc224e4f6106da75a7b55bf79a474f966c6b1ec

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.965892Z digest=sha256:f3210e8f81ce8d27de5e47d813bf3707ced7bec17387bba9ac0bb55188336786

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.968212Z digest=sha256:154f22f24a35066ab0b85666bc695f7a7a7f57b8890060b053087117c7d042d6

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.970927Z digest=sha256:3a65a37b68d7528d3603deb69707f62cb738e636b5a939ec3515cc0b80137f6f

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:cc000049c62d1e0a8f7c4694c09f24ad16784ea3f7b2c337745b1cc193201e04

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

source=pdf_text observed=2026-08-06T12:30:39.976006Z digest=sha256:899a59dd0597205a326e2a634208a1f94e3dc74d693a2281872a9d58d35771aa

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.978374Z digest=sha256:3e485e8d8548a8e18bd6e5b218ae5cedc84a2cc19a7df4797b1eea9197b6ba88

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:d0748b6141549ac521546aa6cc1fce0241ffb54e13b80c69736865b73e185f29

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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verified fuzzy
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.983325Z digest=sha256:8ecc59d67739467a9903b77c56d2ae64864dd35cf963b939407d55013105ba3f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.985637Z digest=sha256:0266e84987dad9f5a31ee650e742e3696d659ea1161aa9b810ceb81d6e05bc9a

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.988019Z digest=sha256:800dee049c2beb31f7ab8e82d565015f354c893cfb75c3a5bf8d5b8fcf9fbd21

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T12:30:39.990628Z digest=sha256:11cc12b72444d79b6ce9384d377101fd39120485f9f36ec2cfa2fbab6b5b8a2a

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T16:20:59.139146Z digest=sha256:fcd60b76944290255b3a2ac46ebbb032891552133781ae0eb57ce7554ac6ac8f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T22:43:20.760265Z digest=sha256:d72323febe360f3d163fc12c368a56fb6dbe69558d58a1ec2af06f85e53a19de

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T01:21:33.692839Z digest=sha256:1a8107f52b4339369cec02f81183a8bbc39a58d50e46e8a4bc243bb626483ba4

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:e771aa5a264c20ed4978a011647d37baa194481cfbe122ca0e425b98cf03926c