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Paper Citation Record · LEDGER

PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert Model

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.08212.

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

pith.paper-citation-record.v1
2411.08212 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T14:50:28.127696Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:28:43.996069Z

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 e83e0882-1c5d-4f7a-9c65-94a13644f928 · inbound

Breaking the MoE LLM Trilemma: Dynamic Expert Clustering with Structured Compression cites this paper.

Breaking the MoE LLM Trilemma: Dynamic Expert Clustering with Structured Compression PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert Model

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-04T14:50:28.127696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T14:50:28.127696Z digest=sha256:6a0852b25ce563127d6f37bf609e7b97de3a4882f644c0c0a8b8b05bf77028ca

Observation 2bc16d6f-e96f-4355-9be5-cf0405ed88df · inbound

EPnG: Adaptive Expert Prune-and-Grow for Parameter-Efficient MoE Fine-tuning cites this paper.

EPnG: Adaptive Expert Prune-and-Grow for Parameter-Efficient MoE Fine-tuning PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert Model

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-07-03T17:28:43.997500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-07-03T17:25:19.699552Z digest=sha256:0f0d0bf8573baa7b78810cbeb561bce889778be91fd450dd7777cdb88bc01485