Paper Citation Record · LEDGER

Multi-objective Large Language Model Alignment with Hierarchical Experts

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2505.20925.

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

pith.paper-citation-record.v1
2505.20925 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T06:42:15.135148Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T06:44:00.909051Z

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 5f0f4e69-596b-49ba-aa4e-8e5cba7b87c9 · inbound

RVPO: Risk-Sensitive Alignment via Variance Regularization cites this paper.

RVPO: Risk-Sensitive Alignment via Variance Regularization Multi-objective Large Language Model Alignment with Hierarchical Experts

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:36:08.511299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 09d5abf9-53d9-4b9c-9549-057fd4459c54 · inbound

Personalizing LLMs with Binary Feedback: A Preference-Corrected Optimization Framework cites this paper.

Personalizing LLMs with Binary Feedback: A Preference-Corrected Optimization Framework Multi-objective Large Language Model Alignment with Hierarchical Experts

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T02:41:17.578387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5b427bf3-3d23-42fa-bc4e-c7baa474d086 · inbound

Common-agency Games for Multi-Objective Test-Time Alignment cites this paper.

Common-agency Games for Multi-Objective Test-Time Alignment Multi-objective Large Language Model Alignment with Hierarchical Experts

Reference 211

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:15:06.567074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 130c807a-55c6-44c1-829a-330ecedfcd38 · inbound

Dynamic Model Merging Made Slim cites this paper.

Dynamic Model Merging Made Slim Multi-objective Large Language Model Alignment with Hierarchical Experts

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-20T15:18:25.432464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f20cef4f-a238-40e9-bd7b-4d76e861ed80 · inbound

SURF: Steering the Scalarization Weight to Uniformly Traverse the Pareto Front cites this paper.

SURF: Steering the Scalarization Weight to Uniformly Traverse the Pareto Front Multi-objective Large Language Model Alignment with Hierarchical Experts

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:44:00.910587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.