Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2309.16620.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T20:48:49.634542Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T07:00:43.286355Z
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 7c5eee10-f120-4418-be25-ed004d944912 · inbound
Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks cites this paper.
Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:48:49.634542Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5b43db33-faff-4cf6-95fc-94e02262e82f · inbound
Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance cites this paper.
Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T11:44:04.869255Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 63d6e3a6-60ec-4bec-98bc-a4a1789fa9ad · inbound
Theory of Optimal Learning Rate Schedules and Scaling Laws for a Random Feature Model cites this paper.
Theory of Optimal Learning Rate Schedules and Scaling Laws for a Random Feature Model Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T07:00:43.288163Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation a83de6b2-e81e-42ef-86e2-07dee3714b8e · inbound
There Will Be a Scientific Theory of Deep Learning cites this paper.
There Will Be a Scientific Theory of Deep Learning Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
Reference 95
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T15:21:09.168848Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 68bcd095-042b-47ed-a5ca-ab7bc458c5f6 · inbound
DeepLoop: Depth Scaling for Looped Transformers cites this paper.
DeepLoop: Depth Scaling for Looped Transformers Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T05:05:25.062788Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.