Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:29:47.615338Z
Paper Citation Record · LEDGER
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain
As of 8 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2505.14906.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
16 of 16 outbound references displayed
- verified exact0
- verified fuzzy11
- unresolved5
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 8d802768-d4b6-4f12-8194-e190e22394b4 · outbound
This paper cites Toward a 6g ai-native air interface,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Toward a 6g ai-native air interface,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:29:49.263855Z
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.
Observation 36e918ec-7957-4608-b2e3-be184fc1f634 · outbound
This paper cites A survey on deep learning for named entity recognition,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain A survey on deep learning for named entity recognition,
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:29:46.323207Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9ffef52d-37c7-4c83-8349-c43017699b97 · outbound
This paper cites Construction of power communication network knowledge graph with bert-bilstm-crf model based entity recognition,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Construction of power communication network knowledge graph with bert-bilstm-crf model based entity recognition,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:29:49.109562Z
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.
Observation 03a8835c-7544-4575-bdd5-6b4516040dec · outbound
This paper cites A multi- entity knowledge joint extraction method of communication equipment faults for industrial iot,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain A multi- entity knowledge joint extraction method of communication equipment faults for industrial iot,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:29:48.953553Z
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.
Observation 3676cab1-ac6e-46c1-84ed-87078aec7b63 · outbound
This paper cites Entity recognition in telecommunications using domain-adapted language models,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Entity recognition in telecommunications using domain-adapted language models,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:29:48.841951Z
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.
Observation c2411bb2-0eee-4e6a-ba4a-343545397b0a · outbound
This paper cites Large language model (llm) for telecommu- nications: A comprehensive survey on principles, key techniques, and opportunities,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Large language model (llm) for telecommu- nications: A comprehensive survey on principles, key techniques, and opportunities,
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:29:46.536929Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 40adf2d7-2ad4-402d-88e1-6de17877f60f · outbound
This paper cites Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Large Language Model (LLM)-enabled In-context Learning for Wireless Network Optimization: A Case Study of Power Control
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:29:46.612991Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 38000fbd-610a-4390-bfd8-c587fe12ce6a · outbound
This paper cites Self-refined generative foundation models for wireless traffic prediction,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Self-refined generative foundation models for wireless traffic prediction,
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:29:46.747046Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2946526c-6501-4927-9984-cce268785544 · outbound
This paper cites Intent-based management of next-generation networks: An llm-centric approach,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Intent-based management of next-generation networks: An llm-centric approach,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:29:48.710950Z
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.
Observation a2549e27-6654-49b4-b4a2-74c04ffa18c5 · outbound
This paper cites Joint Semantic Communication and Target Sensing for 6G Communication System.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Joint Semantic Communication and Target Sensing for 6G Communication System
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:29:46.950866Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dcd879db-a6cd-43a2-95cf-945a904642c8 · outbound
This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Exploring the limits of transfer learning with a unified text-to-text transformer,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:29:48.599469Z
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.
Observation 3d979663-adbd-4f3a-8888-9de2fccb8164 · outbound
This paper cites Alignment-augmented consistent translation for multilingual open information extraction,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Alignment-augmented consistent translation for multilingual open information extraction,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:29:48.512258Z
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.
Observation ed32c21a-3543-4f36-80e8-a62eae0bfd77 · outbound
This paper cites Imojie: Iterative memory-based joint open information extraction,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Imojie: Iterative memory-based joint open information extraction,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:29:48.422604Z
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.
Observation 665e5ca1-9f81-492b-b444-e981ff3bf79d · outbound
This paper cites Neural open information extraction,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Neural open information extraction,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:29:48.273949Z
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.
Observation 6e2988ac-b572-406c-a339-53f6a0fea7c8 · outbound
This paper cites Genie: Generative information extraction,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Genie: Generative information extraction,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:29:48.118422Z
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.
Observation 5d2c9fe6-abf4-4263-8074-75c7f1e0d51b · outbound
This paper cites Adam: A method for stochastic optimization,.
Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domain Adam: A method for stochastic optimization,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:29:47.993040Z
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.
Pith citing papers
No inbound Pith citation observations are available.