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Paper Citation Record · LEDGER

HyperMoE: Towards Better Mixture of Experts via Transferring Among Experts

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.12656.

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

pith.paper-citation-record.v1
2402.12656 v4

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 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:20:34.208984Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T11:36:55.536017Z

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 bd52a66f-475c-4c82-ba3d-b9b4b8f65ba1 · inbound

EvoMoE: Expert Evolution in Mixture of Experts for Multimodal Large Language Models cites this paper.

EvoMoE: Expert Evolution in Mixture of Experts for Multimodal Large Language Models HyperMoE: Towards Better Mixture of Experts via Transferring Among Experts

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:34.208984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:34.208984Z digest=sha256:7da63e8bb377fbad0652505d302b94ee5eca01b345d338c2f23824532fed1d03

Observation 0ebd817a-a2be-47aa-8a36-9740174c8161 · inbound

Projectable Models: One-Shot Generation of Small Specialized Transformers from Large Ones cites this paper.

Projectable Models: One-Shot Generation of Small Specialized Transformers from Large Ones HyperMoE: Towards Better Mixture of Experts via Transferring Among Experts

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T10:20:23.528274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:20:23.528274Z digest=sha256:54dd76b9d6516df9d3238f2f11c9d046c9641184923a6375266d5d37a5ed22cd

Observation dfd1b022-add3-49e3-9c1c-306a6a5ef8b4 · inbound

SDG-MoE: Signed Debate Graph Mixture-of-Experts cites this paper.

SDG-MoE: Signed Debate Graph Mixture-of-Experts HyperMoE: Towards Better Mixture of Experts via Transferring Among Experts

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:06:26.225758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-12T01:20:48.313702Z digest=sha256:b9653e952e425b0df2e2747e85a2d6752acbb0468cbcd5787f06aa79376697e9

Observation 633a543b-73dd-4727-854d-f22a5bd85162 · inbound

SDG-MoE: Signed Debate Graph Mixture-of-Experts cites this paper.

SDG-MoE: Signed Debate Graph Mixture-of-Experts HyperMoE: Towards Better Mixture of Experts via Transferring Among Experts

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:22:28.387198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-13T07:21:44.772644Z digest=sha256:7a7871ec30be608814583080ce06efb9c52dab2d84837e83aec5457cb0aed15e

Observation 7e3ce3b2-fe73-4ac5-8e9d-1896654a8ddc · inbound

Less is MoE: Trimming Experts in Domain-Specialist Language Models cites this paper.

Less is MoE: Trimming Experts in Domain-Specialist Language Models HyperMoE: Towards Better Mixture of Experts via Transferring Among Experts

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-07-02T11:36:55.537616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-28T03:11:23.755739Z digest=sha256:86a0ec542a1a5699cbdff31654154c4266f8d79ee59f7fa377225147734feda9