Paper Citation Record · LEDGER

Efficient Stagewise Pretraining via Progressive Subnetworks

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.05913.

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

pith.paper-citation-record.v1
2402.05913 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 2026-08-11T06:34:44.6726+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:16:59.963976Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T02:06:15.387450Z

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 71129094-cad7-4543-b03e-c1f061da146c · inbound

The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws cites this paper.

The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws Efficient Stagewise Pretraining via Progressive Subnetworks

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T17:16:59.963976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf4e5b96-821d-4b41-a86e-232cf7f3ce8a · inbound

StagFormer: Time Staggering Transformer Decoding for RunningLayers In Parallel cites this paper.

StagFormer: Time Staggering Transformer Decoding for RunningLayers In Parallel Efficient Stagewise Pretraining via Progressive Subnetworks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T14:07:54.852512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e9ebb0e-26f8-44d6-a241-86bae5abbde6 · inbound

Expert Upcycling: Shifting the Compute-Efficient Frontier of Mixture-of-Experts cites this paper.

Expert Upcycling: Shifting the Compute-Efficient Frontier of Mixture-of-Experts Efficient Stagewise Pretraining via Progressive Subnetworks

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-10T03:29:21.472605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7a3170cc-eb5b-40f4-89ef-4eb1d12ad29d · inbound

Expert Upcycling: Shifting the Compute-Efficient Frontier of Mixture-of-Experts cites this paper.

Expert Upcycling: Shifting the Compute-Efficient Frontier of Mixture-of-Experts Efficient Stagewise Pretraining via Progressive Subnetworks

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:06:15.389424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.