Paper Citation Record · LEDGER

UNIC: Universal Classification Models via Multi-teacher Distillation

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2408.05088.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2408.05088 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:57:13.606385Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-02T02:36:27.219180Z

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 8a7ea98c-436e-4a62-ac70-51cc31ec0f2c · inbound

Active Data Curation Effectively Distills Large-Scale Multimodal Models cites this paper.

Active Data Curation Effectively Distills Large-Scale Multimodal Models UNIC: Universal Classification Models via Multi-teacher Distillation

Reference 135

Resolution: unresolved; no resolver link, observed 2026-08-12T11:06:36.217855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd6cd192-a0d9-4d6b-96d8-86c423856e5f · inbound

UNIFORM: Unifying Knowledge from Large-scale and Diverse Pre-trained Models cites this paper.

UNIFORM: Unifying Knowledge from Large-scale and Diverse Pre-trained Models UNIC: Universal Classification Models via Multi-teacher Distillation

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T16:57:13.606385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 432951dc-cc0e-4d79-84ac-26562d009f2a · inbound

SigLino: Efficient Multi-Teacher Distillation for Agglomerative Vision Foundation Models cites this paper.

SigLino: Efficient Multi-Teacher Distillation for Agglomerative Vision Foundation Models UNIC: Universal Classification Models via Multi-teacher Distillation

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-16T20:23:23.722973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 68985b16-c989-431f-bc85-b6e9b03e0d89 · inbound

PRISM: Synergizing Vision Foundation Models via Self-organized Expert Specialization cites this paper.

PRISM: Synergizing Vision Foundation Models via Self-organized Expert Specialization UNIC: Universal Classification Models via Multi-teacher Distillation

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T02:36:27.220733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.