Paper Citation Record · LEDGER

From Task-Specific Models to Unified Systems: A Review of Model Merging Approaches

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2503.08998.

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

pith.paper-citation-record.v1
2503.08998 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 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T17:57:25.190738Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T23:39:03.966708Z

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 5f9ff169-ae66-4b1d-a934-83d65cf716f6 · inbound

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble cites this paper.

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble From Task-Specific Models to Unified Systems: A Review of Model Merging Approaches

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:25:19.524108Z

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.

Observation 0ccbf1cf-3a24-4622-b68b-147a3b87ef4f · inbound

Dropping Experts, Recombining Neurons: Retraining-Free Pruning for Sparse Mixture-of-Experts LLMs cites this paper.

Dropping Experts, Recombining Neurons: Retraining-Free Pruning for Sparse Mixture-of-Experts LLMs From Task-Specific Models to Unified Systems: A Review of Model Merging Approaches

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-04T17:57:25.190738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57b84b5b-7895-4ce3-aec2-dc4e9640b939 · inbound

PACT: Preserving Anchored Cores in Task-vectors for Model Merging cites this paper.

PACT: Preserving Anchored Cores in Task-vectors for Model Merging From Task-Specific Models to Unified Systems: A Review of Model Merging Approaches

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-03T23:39:03.969466Z

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.

Observation 5f866290-39fb-4028-a590-e8b6045638d9 · inbound

Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs cites this paper.

Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs From Task-Specific Models to Unified Systems: A Review of Model Merging Approaches

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-01T06:05:56.852664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.