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Paper Citation Record · LEDGER

Merging Vision Transformers from Different Tasks and Domains

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.16240.

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

pith.paper-citation-record.v1
2312.16240 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 2026-08-03T19:16:03.288029Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T22:16:04.846376Z

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 a5d3eaff-8bf3-4881-848f-4a2a16816044 · inbound

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities cites this paper.

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities Merging Vision Transformers from Different Tasks and Domains

Reference 276

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:16:04.848164Z

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=pdf_text observed=2026-05-17T22:16:04.386706Z digest=sha256:5dfb3f9d18b70324f8daa75f834ffe178556fe045de5f89b2fa172fc8bba8c4d

Observation be94f38f-ed2a-4a70-b9de-248fdc155acf · inbound

Stay Unique, Stay Efficient: Preserving Model Personality in Multi-Task Merging cites this paper.

Stay Unique, Stay Efficient: Preserving Model Personality in Multi-Task Merging Merging Vision Transformers from Different Tasks and Domains

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-03T19:16:03.288029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T19:16:03.288029Z digest=sha256:66ba2d05dc0ae6be3e5fd8333c5a92e1727248c2c907e35a35ffcbe7b73f1692