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Paper Citation Record · LEDGER

Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2408.07254.

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

pith.paper-citation-record.v1
2408.07254 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:55:22.681539Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T04:31:03.682338Z

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 7f4c4f88-00bf-4869-b8ba-ff83366998d1 · inbound

Optimal Spectral Transitions in High-Dimensional Multi-Index Models cites this paper.

Optimal Spectral Transitions in High-Dimensional Multi-Index Models Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-09T11:55:22.681539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:55:22.681539Z digest=sha256:0926d4d343ded8f719df7d03c566ce6478757570a6e3634dc19c7cf23877c21a

Observation 76038ca5-b51d-486f-9a90-54834a59fc4f · inbound

Feature learning is decoupled from generalization in high capacity neural networks cites this paper.

Feature learning is decoupled from generalization in high capacity neural networks Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T14:17:37.159912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:17:37.159912Z digest=sha256:b3f39b9023fcb673612df00dc1173e9c420be8bb7ff8c820d0b0d7ca09151c76

Observation d6a2b444-565f-491b-9b2c-2e9cd232bbc9 · inbound

Uniform-in-Time Weak Propagation-of-Chaos in Shallow Neural Networks cites this paper.

Uniform-in-Time Weak Propagation-of-Chaos in Shallow Neural Networks Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-22T04:31:03.685901Z

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.

source=pdf_text observed=2026-05-22T04:30:48.081597Z digest=sha256:e96bf80ba997a784dbf627e34b206403d7179dde2db6346c14386299d717e2fd