Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Unveiling the Generalization Power of Fine-Tuned Large Language Models
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.09162.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T13:52:26.453086Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T04:27:36.191301Z
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 db56aaf5-0114-4e5f-8d9a-dbbcf4f9672a · inbound
Evolution of Thought: Diverse and High-Quality Reasoning via Multi-Objective Optimization cites this paper.
Evolution of Thought: Diverse and High-Quality Reasoning via Multi-Objective Optimization Unveiling the Generalization Power of Fine-Tuned Large Language Models
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T13:52:26.453086Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 937694b1-a500-4fa1-ad22-2fbaf65fc05f · inbound
Boosting LLM-based Relevance Modeling with Distribution-Aware Robust Learning cites this paper.
Boosting LLM-based Relevance Modeling with Distribution-Aware Robust Learning Unveiling the Generalization Power of Fine-Tuned Large Language Models
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:04:35.946792Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8ab51ba0-e826-4677-829f-f22f171957ef · inbound
The potential -- and the pitfalls -- of using pre-trained language models as cognitive science theories cites this paper.
The potential -- and the pitfalls -- of using pre-trained language models as cognitive science theories Unveiling the Generalization Power of Fine-Tuned Large Language Models
Reference 107
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:01:28.285307Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41ec19c3-055f-47f9-b14e-5d54eae75bd8 · inbound
Filling the Gaps: Selective Knowledge Augmentation for LLM Recommenders cites this paper.
Filling the Gaps: Selective Knowledge Augmentation for LLM Recommenders Unveiling the Generalization Power of Fine-Tuned Large Language Models
Reference 54
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T06:31:01.559546Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c78367f1-e9c2-480b-89a4-bf570428d637 · inbound
Data-Driven Automation cites this paper.
Data-Driven Automation Unveiling the Generalization Power of Fine-Tuned Large Language Models
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T04:27:36.192949Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.