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Paper Citation Record · LEDGER

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN

As of 14 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2608.06789.

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

pith.paper-citation-record.v1
2608.06789 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:53:12.299183Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

  • verified exact1
  • verified fuzzy9
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dafefeb2-32f0-4545-bd17-e5c5bbd9751f · outbound

This paper cites Un- derstanding O-RAN: Architecture, interfaces, algorithms , security, and research challenges,.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN Un- derstanding O-RAN: Architecture, interfaces, algorithms , security, and research challenges,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:12.608932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T20:53:12.225257Z digest=sha256:9ef4300143b70ec9687a2e0018e944743f3ca5ff4366b295e7faec0bfd3f5426

Observation d224d70f-08a5-4577-a53c-3966d3b677ca · outbound

This paper cites Resource allocation for network slicing in open RAN: A hier archical learning approach,.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN Resource allocation for network slicing in open RAN: A hier archical learning approach,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:12.594210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T20:53:12.230653Z digest=sha256:64575338f1cb8482006cc7e1e1bdf02304a2310c1f73ec28ea3d4a882adb57b7

Observation 21761f9f-d8ee-40c2-8f8f-e2108c9fd9c1 · outbound

This paper cites LLM-empowered resource allocation i n wireless communications systems,.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN LLM-empowered resource allocation i n wireless communications systems,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:12.578639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T20:53:12.235547Z digest=sha256:3cf1dd840b5996cda02810b874b4c834c0d17125801982475e82f2f15ce652d0

Observation f0672dfc-3b55-4a9d-84d5-7b47971d0862 · outbound

This paper cites Prompting Wireless Networks: Reinforced In-Context Learning for Power Control.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN Prompting Wireless Networks: Reinforced In-Context Learning for Power Control

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-10T20:53:12.459481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T20:53:12.240827Z digest=sha256:b90afbbbd8c6ce1e65d266a7c93200372d82d4f6ec09ba9c6203b3934b9b385b

Observation 4c893aee-672e-41be-a067-7b28abd34856 · outbound

This paper cites LLM- hRIC: LLM-empowered hierarchical RAN intelligent control for O-RAN,.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN LLM- hRIC: LLM-empowered hierarchical RAN intelligent control for O-RAN,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:12.562024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T20:53:12.246141Z digest=sha256:70789b64f606f65c8f1893960f36dba2f03f9f910e806f8d882c36a1251d5b34

Observation 8716ad8e-6326-4912-aaaa-826263b9df72 · outbound

This paper cites LLM4WM: Adap ting LLM for wireless multi-tasking,.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN LLM4WM: Adap ting LLM for wireless multi-tasking,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:12.543180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T20:53:12.251834Z digest=sha256:b7bf38558983ebcc40a0fe62e87e18cb861d0a3157bf1273ab166871c5d420b6

Observation adc832b7-70bb-4a32-b7a8-182b35763091 · outbound

This paper cites Empowering large language models in wireless communi cation: A novel dataset and fine-tuning framework,.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN Empowering large language models in wireless communi cation: A novel dataset and fine-tuning framework,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:12.524441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T20:53:12.257547Z digest=sha256:d2ed021c40e0840dac8c085a113305483c6aa8921c37e7e7f0c7e195d8136ef4

Observation 46d0eb53-e533-4178-88dd-2e1641651403 · outbound

This paper cites Mobile-LLaMA: Instr uction fine-tuning open-source LLM for network analysis in 5G netwo rks,.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN Mobile-LLaMA: Instr uction fine-tuning open-source LLM for network analysis in 5G netwo rks,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:12.508672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T20:53:12.262276Z digest=sha256:1f8f8aa332171590b8cf6fd829d486e4a68d4fad6de53b6fb52433185dc124b5

Observation 5c360667-5fde-4172-aef7-a9a0500c03f3 · outbound

This paper cites ORAN-Bench-13K: An open source bench- mark for assessing LLMs in open radio access networks,.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN ORAN-Bench-13K: An open source bench- mark for assessing LLMs in open radio access networks,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:12.491605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T20:53:12.267334Z digest=sha256:d812cd0ef4f3d1f1095bde5d793b2a1bab1c25526886b24025ef0b3e47a4498e

Observation d9ba0ed0-8143-432e-bbba-0fb40675d299 · outbound

This paper cites LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T20:53:12.272937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:53:12.272937Z digest=sha256:622f1bbb242b1d0400360cd49055c4bd779b720a4a0fef6d1345dfe992db845e

Observation c44b7b6f-1cca-479e-803d-f3d68813f997 · outbound

This paper cites Rethinking KL regu larization in RLHF: From value estimation to gradient optimization,.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN Rethinking KL regu larization in RLHF: From value estimation to gradient optimization,

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T20:53:12.278491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:53:12.278491Z digest=sha256:511e5b59d3a3f183672708c8040b9f97b4c0e57530f05ba9c71ed31392e80d74

Observation cb88ee21-f6bb-41b5-8074-ac44e4d75faa · outbound

This paper cites The Llama 3 Herd of Models.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN The Llama 3 Herd of Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-10T20:53:12.283532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:53:12.283532Z digest=sha256:249f2b33a22394b2157fdd69c51f32ad0bb1776b2e9b7526aed3aa5683166497

Observation e071dc90-119b-48dc-ae11-3fda933bdda2 · outbound

This paper cites DeepSeek-V3 Technical Report.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN DeepSeek-V3 Technical Report

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T20:53:12.288755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:53:12.288755Z digest=sha256:7825792d1413a919bb70aafaaeb1fd5c2a42939b87bc733792b9ab06af15142c

Observation f315c6d5-a956-40f0-80da-e1c557de6934 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T20:53:12.293955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:53:12.293955Z digest=sha256:fd6fa8d07bb509e2772500b055672786736df5ab3ef79f67bbfc205dcefbc259

Observation cc511ca8-22db-464a-9d5b-a8120b93e562 · outbound

This paper cites CVXPY: A Python-embedded model ing lan- guage for convex optimization,.

EvoRIC: Reinforcement Learning Fine-Tuned LLM-empowered RAN Intelligent Control Toward Autonomous O-RAN CVXPY: A Python-embedded model ing lan- guage for convex optimization,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T20:53:12.476182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T20:53:12.299183Z digest=sha256:e7268bb1b93d0be49265ffd49f6423e8e8bace772f0a0f2c4401cb0104b4e87f

Pith citing papers

No inbound Pith citation observations are available.