Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T19:17:15.350165Z
Paper Citation Record · LEDGER
Universality of Benign Overfitting in Binary Linear Classification
As of 10 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 2 inbound Pith citation observations for arXiv:2501.10538.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:33:59.357786Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T11:34:03.290997Z
Reference resolution
14 of 14 outbound references displayed
- verified exact0
- verified fuzzy6
- unresolved7
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation d41e6a53-8b45-4c54-933c-d37416442252 · outbound
This paper cites an unresolved cited work.
Universality of Benign Overfitting in Binary Linear Classification Unresolved cited work
Reference 2
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T19:17:15.588093Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 11f8028d-0db8-4457-93f6-bfc05ea794b6 · outbound
This paper cites an unresolved cited work.
Universality of Benign Overfitting in Binary Linear Classification Unresolved cited work
Reference 3
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T19:17:15.572219Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 1e6dd279-cced-4253-9eb9-6a0ccde416a2 · outbound
This paper cites Thus, by Lemma S2.5 (i), 𝑡≤ 𝛼2 2 1−𝜀∥ 𝝁∥2 <∥ 𝝁∥2.
Universality of Benign Overfitting in Binary Linear Classification Thus, by Lemma S2.5 (i), 𝑡≤ 𝛼2 2 1−𝜀∥ 𝝁∥2 <∥ 𝝁∥2
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T19:17:15.556982Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 7672bc23-d73e-4d4a-a19f-040632277ccc · outbound
This paper cites an unresolved cited work.
Universality of Benign Overfitting in Binary Linear Classification Unresolved cited work
Reference 5
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T19:17:15.528429Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 73260d62-5133-4b25-8c66-b09007bdf884 · outbound
This paper cites Then, we have ∥ ˆ𝒘∥ ⟨ ˆ𝒘, 𝝁⟩ 2 ≍ 1 ∥ 𝝁∥2+ 1 𝑛𝜌∥ 𝝁∥4.
Universality of Benign Overfitting in Binary Linear Classification Then, we have ∥ ˆ𝒘∥ ⟨ ˆ𝒘, 𝝁⟩ 2 ≍ 1 ∥ 𝝁∥2+ 1 𝑛𝜌∥ 𝝁∥4
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T19:17:15.513960Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 9c5b03cc-f70d-4b66-8c14-b2b5ea258521 · outbound
This paper cites By Lemma S2.1, to conclude that ˆ𝒘=𝑋⊤(𝑋𝑋⊤)−1 𝒚N, it suffices to show that each entry of the vectorΔ( 𝒚N)(𝑋𝑋⊤)−1 𝒚N is strictly positive.
Universality of Benign Overfitting in Binary Linear Classification By Lemma S2.1, to conclude that ˆ𝒘=𝑋⊤(𝑋𝑋⊤)−1 𝒚N, it suffices to show that each entry of the vectorΔ( 𝒚N)(𝑋𝑋⊤)−1 𝒚N is strictly positive
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T19:17:15.499174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d599aed5-c994-4ed2-a279-9a856295214e · outbound
This paper cites an unresolved cited work.
Universality of Benign Overfitting in Binary Linear Classification Unresolved cited work
Reference 9
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T19:17:15.466849Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4f19c7a9-1d9f-4677-beff-dce492af9b52 · outbound
This paper cites The conclusion follows from this result combined with the fact that 𝜌= E[𝑔−2]tr(Σ)−1.
Universality of Benign Overfitting in Binary Linear Classification The conclusion follows from this result combined with the fact that 𝜌= E[𝑔−2]tr(Σ)−1
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T19:17:15.450565Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4deae07d-dfc8-4f45-95e7-5b8cb7b738d1 · outbound
This paper cites an unresolved cited work.
Universality of Benign Overfitting in Binary Linear Classification Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T19:17:15.434643Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 75ebab15-8184-4bb1-9402-7ba1e9a6ff37 · outbound
This paper cites an unresolved cited work.
Universality of Benign Overfitting in Binary Linear Classification Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T19:17:15.419468Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation f472c055-61c5-407b-be9a-6b383edccbb0 · outbound
This paper cites We now show that the conditions in (i) in the present theorem imply the conditions in (i) of(𝑁𝐶2,𝜂).
Universality of Benign Overfitting in Binary Linear Classification We now show that the conditions in (i) in the present theorem imply the conditions in (i) of(𝑁𝐶2,𝜂)
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T19:17:15.404513Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation baf576fa-f159-414c-ba8a-9e0630f4b88a · outbound
This paper cites The conclusion now follows by Theorem 3.5.
Universality of Benign Overfitting in Binary Linear Classification The conclusion now follows by Theorem 3.5
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T19:17:15.387824Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 0222768b-d37e-4c71-8eea-99f33026a15c · outbound
This paper cites an unresolved cited work.
Universality of Benign Overfitting in Binary Linear Classification Unresolved cited work
Reference 32
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T19:17:15.543080Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation a3be4e21-a7c2-4293-8ad8-099cac527338 · outbound
This paper cites Next, we bound each of the remaining values in (S.9).
Universality of Benign Overfitting in Binary Linear Classification Next, we bound each of the remaining values in (S.9)
Reference 64
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-10T19:17:15.483321Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Pith citing papers
Observation 770f3cef-4b79-4cbe-aded-52927f392196 · inbound
Benign Overfitting in Linear Classifiers with a Bias Term cites this paper.
Benign Overfitting in Linear Classifiers with a Bias Term Universality of Benign Overfitting in Binary Linear Classification
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T06:53:08.154080Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 45b56ba1-5165-4e32-8e96-cc6796246d26 · inbound
Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification cites this paper.
Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification Universality of Benign Overfitting in Binary Linear Classification
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:34:03.392749Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.