Paper Citation Record · LEDGER

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing

As of 8 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 1 inbound Pith citation observation for arXiv:2506.00574.

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

pith.paper-citation-record.v1
2506.00574 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:07:29.552481Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-09T18:08:22.254404Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T16:16:09.950875Z

Reference resolution

20 of 20 outbound references displayed

verified exact0
verified fuzzy12
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a1c66c46-b0a3-4927-88ef-0def22da25fd · outbound

This paper cites Near-real-time ran intelligent controller use cases and requirements,.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Near-real-time ran intelligent controller use cases and requirements,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:07:31.337687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 06d397cf-6ede-42e9-a266-a590bf52b4a5 · outbound

This paper cites Study on enhanced access to and support of network slices,.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Study on enhanced access to and support of network slices,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:07:31.232930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9523283f-bb75-48f8-b08e-592da4889d5d · outbound

This paper cites Understanding o-ran: Architecture, interfaces, algo- rithms, security, and research challenges,.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Understanding o-ran: Architecture, interfaces, algo- rithms, security, and research challenges,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:07:31.129200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 26a46a1e-3a7d-4a34-bdae-9921945c7af7 · outbound

This paper cites Meta reinforcement learning approach for adaptive resource optimization in o-ran,.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Meta reinforcement learning approach for adaptive resource optimization in o-ran,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:07:31.027863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation afa5256e-ecc5-46a9-b709-5e6169ede59a · outbound

This paper cites Resource management in wireless networks via multi-agent deep reinforcement learning,.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Resource management in wireless networks via multi-agent deep reinforcement learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:07:30.876159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4697237b-7aa4-447c-a3c9-e75c055ccc25 · outbound

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

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Large generative ai models for telecom: The next big thing?,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:07:30.729209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d2f4a5e9-30a6-465e-8fba-934725ae81b2 · outbound

This paper cites Understanding telecom language through large language models,.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Understanding telecom language through large language models,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:07:30.625444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 911f9646-0b4a-4f7f-a32b-6edd3c20e914 · outbound

This paper cites Communication and Control Co-Design in 6G: Sequential Decision-Making with LLMs.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Communication and Control Co-Design in 6G: Sequential Decision-Making with LLMs

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T12:07:28.373319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef875b7b-42a1-4149-bd94-6af4faba70e0 · outbound

This paper cites Llm-augmented deep reinforcement learning for dynamic o-ran network slicing,.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Llm-augmented deep reinforcement learning for dynamic o-ran network slicing,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:07:30.459567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f2e206b4-a6eb-4550-a676-f94d5ec04f72 · outbound

This paper cites LLM-Based Intent Processing and Network Optimization Using Attention-Based Hierarchical Reinforcement Learning.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing LLM-Based Intent Processing and Network Optimization Using Attention-Based Hierarchical Reinforcement Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T12:07:28.577785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fca70169-69c1-47d5-96e9-f7073477ed64 · outbound

This paper cites Controlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approach.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Controlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approach

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T12:07:28.667152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69417e3c-eead-4211-bfef-ef06e0ad6bcc · outbound

This paper cites LLM-Empowered State Representation for Reinforcement Learning.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing LLM-Empowered State Representation for Reinforcement Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:07:28.753855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 072c0ff2-6638-42e4-a7c8-0d353afda787 · outbound

This paper cites Lora: Low-rank adaptation of large language models.,.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Lora: Low-rank adaptation of large language models.,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:07:30.364930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 357ae171-df55-461f-84df-e9cb323eef4d · outbound

This paper cites Parameter-efficient transfer learning for nlp,.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Parameter-efficient transfer learning for nlp,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:07:30.225948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9a685bc6-fc3d-4d55-b484-dc57f6a195bb · outbound

This paper cites ORANSight-2.0: Foundational LLMs for O-RAN.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing ORANSight-2.0: Foundational LLMs for O-RAN

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T12:07:29.086211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02c5b6a3-6bae-4ef4-b2e3-ba643fc972f5 · outbound

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

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing ORAN-Bench-13K: An Open Source Benchmark for Assessing LLMs in Open Radio Access Networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:07:29.145496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53a2a448-0bb4-40f4-a964-e9645c0c2ea4 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T12:07:29.248864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed078844-a797-4815-b6ad-faaaa66cc29a · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T12:07:29.363229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5293c7c-839b-48fb-a1b4-2fe5acb25fb2 · outbound

This paper cites Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor,.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:07:30.109076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 29895340-75b6-4cc8-b79c-0a17b07611a1 · outbound

This paper cites 5G; NR; physical channels and modulation,.

Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing 5G; NR; physical channels and modulation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:07:29.928728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation 2ef097d6-dca5-46ad-98d2-5017a38d3c98 · inbound

AIIM: Adaptive Inter-cell Interference Mitigation for Heterogeneous Multi-vendor 5G O-RAN Networks cites this paper.

AIIM: Adaptive Inter-cell Interference Mitigation for Heterogeneous Multi-vendor 5G O-RAN Networks Prompt-Tuned LLM-Augmented DRL for Dynamic O-RAN Network Slicing

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:16:09.956293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.