Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.12204.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:02:26.386830Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T20:43:09.592530Z
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 db602f44-8950-4ac8-8188-df2ca3cbc5cd · inbound
CC-Tuning: A Cross-Lingual Connection Mechanism for Improving Joint Multilingual Supervised Fine-Tuning cites this paper.
CC-Tuning: A Cross-Lingual Connection Mechanism for Improving Joint Multilingual Supervised Fine-Tuning Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:02:26.386830Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7d91cfaf-5882-4ede-88c1-5be018cfc9ee · inbound
Large Language Models for Crash Detection in Video: A Survey of Methods, Datasets, and Challenges cites this paper.
Large Language Models for Crash Detection in Video: A Survey of Methods, Datasets, and Challenges Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages
Reference 60
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T20:43:09.652431Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.