Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2310.15051.
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, observed 2026-08-08T04:38:57.685688Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T21:07:47.007295Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 7fd98052-b612-4b22-b5c8-4518f1423e08 · inbound
Mapping the Landscape of Generative AI in Network Monitoring and Management cites this paper.
Mapping the Landscape of Generative AI in Network Monitoring and Management TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge
Reference 164
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T04:38:57.685688Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b19b359c-b93e-4e8f-adf1-598e8937711d · inbound
NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research cites this paper.
NextG-GPT: Leveraging GenAI for Advancing Wireless Networks and Communication Research TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:19:26.341526Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bcf4d2af-5ec5-44a0-8e26-7743d8ec65f3 · inbound
Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN cites this paper.
Edge Agentic AI Framework for Autonomous Network Optimisation in O-RAN TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T12:30:39.957816Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dbc22e86-7bee-42a3-8ca8-5e7cb2ec04e7 · inbound
MM-Telco: Benchmarks and Multimodal Large Language Models for Telecom Applications cites this paper.
MM-Telco: Benchmarks and Multimodal Large Language Models for Telecom Applications TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T22:10:22.985161Z
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 a676243c-8cec-4182-ab43-bd9edf41b2bd · inbound
Against the Monolithic Wireless World Model: Why NextG Needs Composable and Agentic Intelligence cites this paper.
Against the Monolithic Wireless World Model: Why NextG Needs Composable and Agentic Intelligence TeleQnA: A Benchmark Dataset to Assess Large Language Models Telecommunications Knowledge
Reference 53
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T21:07:47.009268Z
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.