Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2312.04339.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T17:03:16.746943Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-17T22:16:04.552795Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 5405d659-fab2-4564-a559-84899d84efa1 · inbound
Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities Merging by Matching Models in Task Parameter Subspaces
Reference 204
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d399499e-34dc-4109-9d73-28622bd6b344 · inbound
Harnessing Optimization Dynamics for Curvature-Informed Model Merging Merging by Matching Models in Task Parameter Subspaces
Reference 31
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e67ab7d-e9a3-4324-ad88-9759cc133275 · inbound
Rethinking Heterogeneous LLM Merging: A Weighted Model Averaging Perspective Merging by Matching Models in Task Parameter Subspaces
Reference 44
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 32d96f41-490c-48f5-9cae-e869ceddfdcd · inbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Merging by Matching Models in Task Parameter Subspaces
Reference 4
Source-reported events for the cited work
Unavailable: canonical work link unavailable.