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Paper Citation Record · LEDGER

DistilQwen2.5: Industrial Practices of Training Distilled Open Lightweight Language Models

As of 8 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.

pith.paper-citation-record.v1
2504.15027 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:49:12.683332Z

measured 0 of 1 external citation measurements

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.

source=arxiv_source observed=2026-08-07T13:49:12.683332Z digest=sha256:e152395430f383102f867e2628baf0cca00451b76584336ed2c0c1fe93a1e065

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-13T01:25:14.540277Z digest=sha256:518f228fa5bca11e85cad0340e9340a5bb07623015351075718147ca04ae6dbb