Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2403.07384.
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 2026-08-09T10:26:07.012786Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T05:30:57.923050Z
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 3cdad77c-5806-4c65-a766-405eb59b9d5f · inbound
Training an LLM-as-a-Judge Model: Pipeline, Insights, and Practical Lessons cites this paper.
Training an LLM-as-a-Judge Model: Pipeline, Insights, and Practical Lessons SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T10:26:07.012786Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 12886857-c64a-46bf-bb63-0f7df68c5661 · inbound
GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation cites this paper.
GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T17:31:59.916976Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9830cd1c-a07b-4a30-be4a-40ff3f62aab7 · inbound
GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization cites this paper.
GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models
Reference 77
- Resolution
- malformed identifier
- arxiv_id, observed 2026-05-11T05:30:57.928515Z
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.