Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DistilQwen2.5: Industrial Practices of Training Distilled Open Lightweight Language Models
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2504.15027.
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 2026-08-07T13:49:12.683332Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T01:27:01.869561Z
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 35b5faeb-9949-487f-a486-51f21beaea05 · inbound
EasyDistill: A Comprehensive Toolkit for Effective Knowledge Distillation of Large Language Models cites this paper.
EasyDistill: A Comprehensive Toolkit for Effective Knowledge Distillation of Large Language Models DistilQwen2.5: Industrial Practices of Training Distilled Open Lightweight Language Models
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:49:12.683332Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7d129878-0934-4e1a-bfc5-3a4918a6951a · inbound
OmniThoughtVis: A Scalable Distillation Pipeline for Deployable Multimodal Reasoning Models cites this paper.
OmniThoughtVis: A Scalable Distillation Pipeline for Deployable Multimodal Reasoning Models DistilQwen2.5: Industrial Practices of Training Distilled Open Lightweight Language Models
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T01:27:01.872001Z
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.