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Paper Citation Record · LEDGER

Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.12034.

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

pith.paper-citation-record.v1
2406.12034 v2

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 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:36:34.874121Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T22:16:04.800890Z

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 74493416-e500-41ef-a1f3-95a84cef29de · 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 Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts

Reference 107

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:16:04.803434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-17T22:16:04.386706Z digest=sha256:c1616a63ad87f74e1025e440295dee86ecc62d1326c0fac0bd206e2a7feb94be

Observation e891e19e-efe5-455b-b531-266ec30aa7ac · inbound

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts

Reference 156

Resolution
unresolved
no resolver link, observed 2026-08-06T21:36:34.874121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:36:34.874121Z digest=sha256:36d4f685df37dff3dd7fd68b788d09ddb9ff8c87daf5ccc1d5dcc5794a63ec14

Observation ca94fb1a-cca3-4038-b2e5-9430a494c013 · inbound

PolicyLLM: Towards Excellent Comprehension of Public Policy for Large Language Models cites this paper.

PolicyLLM: Towards Excellent Comprehension of Public Policy for Large Language Models Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:31:03.306384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T15:59:34.133124Z digest=sha256:9f5edb53d9487f1703d5a6fbb2d8c462ff8d132981ffc0abb0a48bc58b6f3d6a

Observation 767905fa-3b14-4241-8164-9bc7abea59e2 · inbound

Modular Foundation Models for Time-Series Perception in Digital Twins cites this paper.

Modular Foundation Models for Time-Series Perception in Digital Twins Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-12T01:22:51.284207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T01:22:51.284207Z digest=sha256:d4f455c181690117c659bd066d7a6693981daa93dd9662506c38c730665a3590