Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
TrainerAgent: Customizable and Efficient Model Training through LLM-Powered Multi-Agent System
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2311.06622.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T18:07:36.987671Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T21:52:10.302235Z
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 58fe0df8-49d3-4229-a710-263d2efdac00 · inbound
Boosting Private Domain Understanding of Efficient MLLMs: A Tuning-free, Adaptive, Universal Prompt Optimization Framework cites this paper.
Boosting Private Domain Understanding of Efficient MLLMs: A Tuning-free, Adaptive, Universal Prompt Optimization Framework TrainerAgent: Customizable and Efficient Model Training through LLM-Powered Multi-Agent System
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T00:08:16.236079Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5520bb3f-8c4a-41ba-9edc-121492b60a72 · inbound
Large Language Model Agent: A Survey on Methodology, Applications and Challenges cites this paper.
Large Language Model Agent: A Survey on Methodology, Applications and Challenges TrainerAgent: Customizable and Efficient Model Training through LLM-Powered Multi-Agent System
Reference 61
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T21:52:10.305336Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation a1bdd310-d3fb-4987-ae18-d5bde35453e8 · inbound
Adaptive Learning Systems: Personalized Curriculum Design Using LLM-Powered Analytics cites this paper.
Adaptive Learning Systems: Personalized Curriculum Design Using LLM-Powered Analytics TrainerAgent: Customizable and Efficient Model Training through LLM-Powered Multi-Agent System
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T18:07:36.987671Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.