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Paper Citation Record · LEDGER

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems

As of 16 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2506.12490.

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

pith.paper-citation-record.v1
2506.12490 v2

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T01:10:39.240949Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

22 of 22 outbound references displayed

  • verified exact0
  • verified fuzzy19
  • unresolved3
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ce50842e-d0c5-44d5-be67-5ae24a0f4407 · outbound

This paper cites Fighting bandits with a new kind of smoothness.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Fighting bandits with a new kind of smoothness

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:43.438222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation e1c9d1ec-09fd-491e-947d-0e21910a08dd · outbound

This paper cites Regret in online combinatorial optimization.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Regret in online combinatorial optimization

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:43.174127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:37.381016Z digest=sha256:70b4c5b0f7a47a9eeee9b923669d0c4f61d2fbccff36477e5b04689bfb84df39

Observation 7c965ff0-6b57-4bb8-8507-902ccde2eb2c · outbound

This paper cites Geometric resampling in nearly linear time for follow-the-perturbed-leader with best-of-both-worlds guarantee in bandit problems.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Geometric resampling in nearly linear time for follow-the-perturbed-leader with best-of-both-worlds guarantee in bandit problems

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:42.934456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 9dda6306-5540-4f99-98dd-59e22f093e83 · outbound

This paper cites Combinatorial multi-armed bandit: General framework and applications.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Combinatorial multi-armed bandit: General framework and applications

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:42.648126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:37.594589Z digest=sha256:2db75ae886cdd3489d52ab61f35353765a1fc0597052d3a48b0c5ccd9fb450b4

Observation d22bd4bc-3875-4e79-bdfa-b181afe6b21a · outbound

This paper cites Combinatorial network optimization with unknown variables: Multi-armed bandits with linear rewards and individual observations.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Combinatorial network optimization with unknown variables: Multi-armed bandits with linear rewards and individual observations

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:42.367380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 1ebe5827-2a83-4e8b-b0cc-ecc2ff7bcdad · outbound

This paper cites Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:42.113649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:37.797038Z digest=sha256:40efe999fce60b1eb04ac5958aa1d34dbbe2c7fa9124fe5dfbde9cd1dfd1abcb

Observation e1d098f5-f577-4504-a9d5-fc893191b6c2 · outbound

This paper cites Hybrid regret bounds for combinatorial semi-bandits and adversarial linear bandits.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Hybrid regret bounds for combinatorial semi-bandits and adversarial linear bandits

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:41.887039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:37.895960Z digest=sha256:97adcdd85f8866f8789095ee7e8731db9d62b2713f72534c2c78e685421f0fc0

Observation c6013070-d1ef-46ed-a0bf-97b5ed21500f · outbound

This paper cites Matroid bandits: fast combinatorial optimization with learning.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Matroid bandits: fast combinatorial optimization with learning

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:41.710403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:37.986231Z digest=sha256:49f567f3186b66420bbb95e237c5360fdd769473e9ac129942fdfd7272a63062

Observation 869c4262-d63a-477c-bc80-249f4f52bc1d · outbound

This paper cites Tight regret bounds for stochastic combinatorial semi-bandits.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Tight regret bounds for stochastic combinatorial semi-bandits

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:41.565269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:38.065751Z digest=sha256:5221c8297e9731769fcc4b2b5ff14b15e6871725ae091fc9cf132414056e69f5

Observation 66b0766a-0e33-454e-9afc-2ec65ef96ea9 · outbound

This paper cites Follow-the-perturbed-leader with fréchet-type tail distributions: Optimality in adversarial bandits and best-of-both-worlds.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Follow-the-perturbed-leader with fréchet-type tail distributions: Optimality in adversarial bandits and best-of-both-worlds

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:41.384464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:38.139137Z digest=sha256:d10924d41d4146faa488b1f1be883ffd18587451dcf019da71a5b0ebc85cea18

Observation 481f619a-dde7-462c-b189-559026062428 · outbound

This paper cites Exact moments of order statistics from the pareto distribution.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Exact moments of order statistics from the pareto distribution

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:41.167370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:38.223142Z digest=sha256:5778d90b386acb07b96997d947e929676922faf49cfe46560127e1b8c607d936

Observation 95f2b1c0-9106-406d-84a4-21e4d1287c9b · outbound

This paper cites First-order regret bounds for combinatorial semi-bandits.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems First-order regret bounds for combinatorial semi-bandits

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:40.990249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:38.304154Z digest=sha256:795e953df7895473cd768131070b4a9892b3ce18fedecbc2864fb5ef9b59db6f

Observation 287d65e2-6bf5-4cb7-847b-7dc6263d558a · outbound

This paper cites Importance weighting without importance weights: An efficient algorithm for combinatorial semi-bandits.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Importance weighting without importance weights: An efficient algorithm for combinatorial semi-bandits

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:40.747769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:38.405670Z digest=sha256:1485e83428392aa1c98aa6dd1aff15569f6be7e1701dacee656caab157f45b2a

Observation b5a15666-8591-44e9-938b-844c23a95b8a · outbound

This paper cites Online joint bid/daily budget optimization of internet advertising campaigns.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Online joint bid/daily budget optimization of internet advertising campaigns

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:40.516754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:38.502466Z digest=sha256:2bedc9253c3f9490cde14c69fd8fd6b936f4d1aad124b294696782b0b6b66a16

Observation 87ddbfd4-565b-410c-b36b-bf3ac18eadae · outbound

This paper cites Further adaptive best-of-both-worlds algorithm for combinatorial semi-bandits.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Further adaptive best-of-both-worlds algorithm for combinatorial semi-bandits

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:40.307122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:38.581590Z digest=sha256:46107343e91ada05c273d90bb077ab8ab67ace58240aab67d16ac7f301b38896

Observation 8c7be7e1-b75e-417c-b85b-365bbcfb82be · outbound

This paper cites Efficient task assignment for spatial crowdsourcing: A combinatorial fractional optimization approach with semi-bandit learning.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Efficient task assignment for spatial crowdsourcing: A combinatorial fractional optimization approach with semi-bandit learning

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:40.067515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:38.662715Z digest=sha256:09cfaefc2b3459ca926c371440058268229ac17b8eef8144fe6025f4f1c7568c

Observation bfb29e84-a737-4c12-9c6a-049081ae5306 · outbound

This paper cites Thompson sampling for combinatorial semi-bandits.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Thompson sampling for combinatorial semi-bandits

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:39.866882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:38.783016Z digest=sha256:264542b7babf9741283fc4fe83f17efd05416f6183407f7c6d4648974c2549a3

Observation d24ca6a1-bede-431d-bfbc-e6f1a1062af2 · outbound

This paper cites Efficient ordered combinatorial semi-bandits for whole-page recommendation.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Efficient ordered combinatorial semi-bandits for whole-page recommendation

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:39.685318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:38.890399Z digest=sha256:c3ec6758e661a6023e6214fe19d8978da60594748c250e19f696b9fac4f4672f

Observation 81afac34-0bf8-411e-bc89-bb515e21a1ea · outbound

This paper cites More adaptive algorithms for adversarial bandits.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems More adaptive algorithms for adversarial bandits

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T01:10:38.970333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:10:38.970333Z digest=sha256:5cb9e713b601a31142ec8e4b3af0bb33fffaf6fdd03e2dd9eff58062d204d05a

Observation 7cd1c428-1131-432b-bc61-16bc38b38b2a · outbound

This paper cites Follow-the-Perturbed-Leader Approaches Best-of-Both-Worlds for the m-Set Semi-Bandit Problems.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Follow-the-Perturbed-Leader Approaches Best-of-Both-Worlds for the m-Set Semi-Bandit Problems

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T01:10:39.084987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:10:39.084987Z digest=sha256:6d94cef426bc253cf4597eb5953756b1d346e9454995a1d9cbf0c6c723a55fb7

Observation 682d8edf-3974-403d-9936-f9827df21869 · outbound

This paper cites Tsallis-inf: An optimal algorithm for stochastic and adversarial bandits.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Tsallis-inf: An optimal algorithm for stochastic and adversarial bandits

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T01:10:39.163800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:10:39.163800Z digest=sha256:a4ccad6623b91e5fad401d3cd6665a4df8b625f607f255cee04886428d5fb526

Observation aa7ac782-61e2-47a7-916e-bb30ab4743f9 · outbound

This paper cites Beating stochastic and adversarial semi-bandits optimally and simultaneously.

Note on Follow-the-Perturbed-Leader in Combinatorial Semi-Bandit Problems Beating stochastic and adversarial semi-bandits optimally and simultaneously

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T01:10:39.451752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-07T01:10:39.240949Z digest=sha256:05d0b9f24fdfab86285e4b62d2e1640d787d0d7297738adddae3c18add583f8b

Pith citing papers

No inbound Pith citation observations are available.