Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Semantic-Driven Topic Modeling Using Transformer-Based Embeddings and Clustering Algorithms
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.00134.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T23:54:26.584615Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation b96304a7-401b-49cd-a045-0326dae3a47a · inbound
Automated Unity Game Template Generation from GDDs via NLP and Multi-Modal LLMs cites this paper.
Automated Unity Game Template Generation from GDDs via NLP and Multi-Modal LLMs Semantic-Driven Topic Modeling Using Transformer-Based Embeddings and Clustering Algorithms
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T23:54:26.584615Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3a1a821b-774a-4aa6-a668-2a699b6c7a8d · inbound
Eliot: Interactively $\underline{E}$xploring Fast-Changing Scientific $\underline{Li}$terature Trends with $\underline{O}$nline Da$\underline{t}$a and Learning cites this paper.
Eliot: Interactively $\underline{E}$xploring Fast-Changing Scientific $\underline{Li}$terature Trends with $\underline{O}$nline Da$\underline{t}$a and Learning Semantic-Driven Topic Modeling Using Transformer-Based Embeddings and Clustering Algorithms
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T15:33:32.093642Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.