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Paper Citation Record · LEDGER

Optimal Rates for Learning with Monotone Adversaries

As of 15 August 2026, this Paper Citation Record lists 8 of 8 outbound references and 1 inbound Pith citation observation for arXiv:2608.06337.

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

pith.paper-citation-record.v1
2608.06337 v1

Coverage vector

measured 8 of 8 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:19:29.529771Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:35:04.251947Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T05:35:04.585293Z

Reference resolution

8 of 8 outbound references displayed

  • verified exact0
  • verified fuzzy7
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6ad3787b-d047-4dc3-af77-ee66bc75e4bd · outbound

This paper cites The Optimal Sample Complexity of PAC Learning.

Optimal Rates for Learning with Monotone Adversaries The Optimal Sample Complexity of PAC Learning

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:29.613862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T05:19:29.519223Z digest=sha256:4531143d19798ec933ce6bd01a5849191d82994eaabe62023e6e9a0735b4b514

Observation f75b6f96-40c9-405c-af93-d452147323e7 · outbound

This paper cites PMLR, 2016, pp.

Optimal Rates for Learning with Monotone Adversaries PMLR, 2016, pp

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:29.663462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T05:19:29.497159Z digest=sha256:445a8d7a7128e44a3f4d96a316986e170483261daa6af6546d519fc4d253516a

Observation 6fe64d4b-f767-4177-a57f-2a6e96e0b195 · outbound

This paper cites Learning in an Echo Chamber: Online Learning with Replay Adversary.

Optimal Rates for Learning with Monotone Adversaries Learning in an Echo Chamber: Online Learning with Replay Adversary

Reference 134

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:29.630293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T05:19:29.514012Z digest=sha256:d116678a7defa0a9aec885b17afe66d07646d934724ce5f2171c53aa42a10eef

Observation 1d21716a-a9b4-4c49-8b95-27d56abb97e8 · outbound

This paper cites Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm.

Optimal Rates for Learning with Monotone Adversaries Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm

Reference 195

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:29.597317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T05:19:29.525009Z digest=sha256:09c78db9d3bf2b338fb9f4b47c9f63808a2027e889b9a20f7e25d814bf46ce80

Observation c1572a63-0cb6-401a-a379-fe236ebb01c9 · outbound

This paper cites Partitioning and Geometric Embedding of Range Spaces of Finite Vapnik–Chervonenkis Dimension.

Optimal Rates for Learning with Monotone Adversaries Partitioning and Geometric Embedding of Range Spaces of Finite Vapnik–Chervonenkis Dimension

Reference 247

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:29.680082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T05:19:29.491769Z digest=sha256:b3202bf3c6f048a70f311822d16b44e3bd97682de0a65ff716e54d0c676036fe

Observation 24b4dfd2-5973-415b-a8a2-58240add9b89 · outbound

This paper cites How Robust are Reconstruction Thresholds for Community Detection?.

Optimal Rates for Learning with Monotone Adversaries How Robust are Reconstruction Thresholds for Community Detection?

Reference 313

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:29.581988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T05:19:29.529771Z digest=sha256:f7855cecbb231480463f0c3d2f52e7f096a8d48f1f76bda298771a70a98f0207

Observation b4d8de35-91e8-4a16-8cba-335628a8a664 · outbound

This paper cites 2 Notes on Classes with Vapnik-Chervonenkis Dimension 1.

Optimal Rates for Learning with Monotone Adversaries 2 Notes on Classes with Vapnik-Chervonenkis Dimension 1

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-07T05:19:29.502696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:19:29.502696Z digest=sha256:89851fc9000672315c0d377d40129e4272eb4fdcf9a6787dc0d9e892da79523f

Observation dba2f80c-3526-419b-9731-7b4f94bc39cd · outbound

This paper cites Robust Learning under Clean-Label Attack.

Optimal Rates for Learning with Monotone Adversaries Robust Learning under Clean-Label Attack

Reference 2026

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:19:29.646555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T05:19:29.507889Z digest=sha256:8d39f583363d639f0989e83c2968f5105677b9b512006a6d8ec91cde87fb48be

Pith citing papers

Observation 0e0fcc7d-6ac6-44cc-beed-a60ad7cfa42d · inbound

Bagging Robustly Learns VC Classes with Linear Sample Complexity cites this paper.

Bagging Robustly Learns VC Classes with Linear Sample Complexity Optimal Rates for Learning with Monotone Adversaries

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-14T05:35:04.589905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-14T05:35:04.251947Z digest=sha256:844f5a8a2cb6e415d044657cef0c735991eddf2386d78d6f049876f17ac62a08