Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.07089.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:44:52.958822Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T08:12:10.638301Z
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 664d1691-2a91-43c5-8dab-6676388a4ea0 · 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 Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic
Reference 101
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T22:16:04.737194Z
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.
Observation e861845f-27cf-443a-addd-d64be5b5b0ce · inbound
DC-TTA: Divide-and-Conquer Framework for Test-Time Adaptation of Interactive Segmentation cites this paper.
DC-TTA: Divide-and-Conquer Framework for Test-Time Adaptation of Interactive Segmentation Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T08:12:10.642572Z
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.
Observation 75ff8316-8028-4dc3-b38a-ede78f0a2170 · inbound
Interaction-Merged Motion Planning: Effectively Leveraging Diverse Motion Datasets for Robust Planning cites this paper.
Interaction-Merged Motion Planning: Effectively Leveraging Diverse Motion Datasets for Robust Planning Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:44:52.958822Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.