Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.10779.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T16:29:11.747946Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T18:33:50.603469Z
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 5b0710bc-2644-48cd-9692-b6ee270aa22e · inbound
HuggingGraph: Understanding the Supply Chain of LLM Ecosystem cites this paper.
HuggingGraph: Understanding the Supply Chain of LLM Ecosystem Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:29:11.747946Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e25cdb47-557a-44b0-990b-10bd0d8c4d88 · inbound
Fast and Accurate Contextual Knowledge Extraction Using Cascading Language Model Chains and Candidate Answers cites this paper.
Fast and Accurate Contextual Knowledge Extraction Using Cascading Language Model Chains and Candidate Answers Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:35:22.445665Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b400e013-5367-4743-8e21-56c27229fecf · inbound
Sustainable Code Generation Using Large Language Models: A Systematic Literature Review cites this paper.
Sustainable Code Generation Using Large Language Models: A Systematic Literature Review Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T18:50:16.679106Z
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 5bf1bbf3-fe34-4ce8-b75a-c2763bdcf7c3 · inbound
Development and Preliminary Evaluation of a Domain-Specific Large Language Model for Tuberculosis Care in South Africa cites this paper.
Development and Preliminary Evaluation of a Domain-Specific Large Language Model for Tuberculosis Care in South Africa Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations
Reference 12
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-14T22:49:33.912136Z
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 e2827631-4aa5-471f-88ba-336d1a65d80b · inbound
Gradient Transformer: Learning to Generate Updates for LLMs cites this paper.
Gradient Transformer: Learning to Generate Updates for LLMs Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T18:33:50.605011Z
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.