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Paper Citation Record · LEDGER

Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.03641.

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

pith.paper-citation-record.v1
2407.03641 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:02:49.305405Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T22:16:04.938641Z

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 b5411824-b695-4e99-a2ab-b26f99993eec · 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 Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy

Reference 124

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:16:04.940982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-17T22:16:04.386706Z digest=sha256:25681e3a3f89a42d7f3b76429f057e6f1aa441716f32c2279ae54e082fdeaeae

Observation 3d1431ea-9386-482a-9145-e3729770bf4d · inbound

How to Merge Your Multimodal Models Over Time? cites this paper.

How to Merge Your Multimodal Models Over Time? Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-11T19:24:43.197297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:24:43.197297Z digest=sha256:6c64dcc11a153fff52bf894e1e4f1daa892f08338ce2587182c346c9a72fe6b4

Observation ce33e99e-f12c-47b3-8911-6b8c0012f999 · inbound

RanDeS: Randomized Delta Superposition for Multi-Model Compression cites this paper.

RanDeS: Randomized Delta Superposition for Multi-Model Compression Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-15T21:02:49.305405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:02:49.305405Z digest=sha256:5554df01ac29acab45b2a5af472e740523095ce01262737b3c8308da4751f21d