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Paper Citation Record · LEDGER

Improved Algorithms for Nash Welfare in Linear Bandits

As of 7 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2601.22969.

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

pith.paper-citation-record.v1
2601.22969 v2

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T06:28:52.145933Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

14 of 14 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b2aed1f-0312-4960-8262-00a55cf423ec · outbound

This paper cites W orks on Nash RegretBarman et al.

Improved Algorithms for Nash Welfare in Linear Bandits W orks on Nash RegretBarman et al

Reference 1

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no resolver link, observed 2026-08-03T06:28:51.708562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:51.708562Z digest=sha256:ea5319c03cb1cb2eda5a6f67fb76097801cda40cb223d837ab41b3c95cfb7313

Observation c918086a-06a4-437c-9177-2f73128e2fb1 · outbound

This paper cites Given the collection of arm vectors, this computation can be carried out efficiently (see Chapter 3 of Todd (2016)).

Improved Algorithms for Nash Welfare in Linear Bandits Given the collection of arm vectors, this computation can be carried out efficiently (see Chapter 3 of Todd (2016))

Reference 2

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no resolver link, observed 2026-08-03T06:28:52.107073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:52.107073Z digest=sha256:07521f84dd3bbed3278b333d3e017fc80665b8f0068ebe86b352165c64c7ca89

Observation b7291213-1832-4f71-bb17-3ba97bf0bfa0 · outbound

This paper cites ForLinUCB(Algorithm 3), each iteration requires O(d2) time for Line 3 and O(|X |) time for Line 4, leading to an overall complexity of O(T d2 + T|X |).

Improved Algorithms for Nash Welfare in Linear Bandits ForLinUCB(Algorithm 3), each iteration requires O(d2) time for Line 3 and O(|X |) time for Line 4, leading to an overall complexity of O(T d2 + T|X |)

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:52.145933Z digest=sha256:9ead0ad77bb9d57e079f8b123daa49ca1a65c4fd03dfc3d56982b1c112aeed33

Observation 73141942-5372-42c7-a403-49226369005d · outbound

This paper cites an unresolved cited work.

Improved Algorithms for Nash Welfare in Linear Bandits Unresolved cited work

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:51.751898Z digest=sha256:4a6bda5cf1e3eacc59762080d19980319e551dcf71096f44878ef0802d96605b

Observation 52658a83-ddd3-444c-acf5-22264a0e1444 · outbound

This paper cites an unresolved cited work.

Improved Algorithms for Nash Welfare in Linear Bandits Unresolved cited work

Reference 9

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unresolved
no resolver link, observed 2026-08-03T06:28:51.816973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:51.816973Z digest=sha256:62b81a67c5e8f47af63d3bcdb1fa91400ea76f90c6fd286934bbe3908452ef7d

Observation fc1dd6ce-7ea0-4c46-809f-d4a1e83e0b9b · outbound

This paper cites 1For a convex body K⊂R d, its John ellipsoid Gr¨ otschel et al.

Improved Algorithms for Nash Welfare in Linear Bandits 1For a convex body K⊂R d, its John ellipsoid Gr¨ otschel et al

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:51.882311Z digest=sha256:7ce08d401a0325b9e9bae4a4689bf6a7fabded005a5d15680337937243d6be03

Observation cc8b49b8-49f2-4c56-b78c-3adab1b26afc · outbound

This paper cites Lemma B.12(Abbasi-Yadkori et al.

Improved Algorithms for Nash Welfare in Linear Bandits Lemma B.12(Abbasi-Yadkori et al

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:51.952184Z digest=sha256:76cf9d89d4f7fb8b8be24521f788db7455f048f286915694d591d71d571fc535

Observation 343b6738-b78d-4ecb-8c79-0da7a473be3f · outbound

This paper cites This implicitly assumes that T > d(d + 1), which is reasonable given that even the minimax optimal rates of O( d√ T ) are vacuous forT= Ω(d 2).

Improved Algorithms for Nash Welfare in Linear Bandits This implicitly assumes that T > d(d + 1), which is reasonable given that even the minimax optimal rates of O( d√ T ) are vacuous forT= Ω(d 2)

Reference 12

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source=pdf_text observed=2026-08-03T06:28:52.033994Z digest=sha256:5159016bc2ff3161419576b22158fa737cbfffc5e8b449ec22cb28fbbc82b999

Observation 88a151be-3274-486f-9f3a-e74e68551a0f · outbound

This paper cites Tractable Fragments of the Maximum Nash Welfare Problem.

Improved Algorithms for Nash Welfare in Linear Bandits Tractable Fragments of the Maximum Nash Welfare Problem

Reference 1993

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no resolver link, observed 2026-08-03T06:28:51.466698Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:51.466698Z digest=sha256:cb47845248057319b12a942ee0f9835f199336cb6a6bd2de0a16c6e077000888

Observation 3b0012d7-579c-4a74-ac26-8eed60c646a9 · outbound

This paper cites Tight Approximation Algorithms for p-Mean Welfare Under Subadditive Valuations.

Improved Algorithms for Nash Welfare in Linear Bandits Tight Approximation Algorithms for p-Mean Welfare Under Subadditive Valuations

Reference 2002

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:51.393882Z digest=sha256:bc54a980ebd8033e5c63a0d5e5017e072202539d5029f5770879bf2802e122ef

Observation 620fda4f-67aa-456c-a40f-e07d7c0f5d95 · outbound

This paper cites Introducing LETOR 4.0 Datasets.

Improved Algorithms for Nash Welfare in Linear Bandits Introducing LETOR 4.0 Datasets

Reference 2004

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source=pdf_text observed=2026-08-03T06:28:51.518661Z digest=sha256:217ab411ea27df65f1507e31e973e4065eb529d986a29c4502c8718d9b15361e

Observation 9def765f-8fb9-49cf-886e-494bff0abee6 · outbound

This paper cites On the fairness of normalized p-means for allocating goods and chores.arXiv preprint arXiv:2402.14996,.

Improved Algorithms for Nash Welfare in Linear Bandits On the fairness of normalized p-means for allocating goods and chores.arXiv preprint arXiv:2402.14996,

Reference 2008

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no resolver link, observed 2026-08-03T06:28:51.425830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:51.425830Z digest=sha256:2dea64ad064a868207fc952aacc6c98c7fef6bbfb920019ab4e60732fba5ffa7

Observation bbce3b96-9dfc-4877-bb22-cce493469936 · outbound

This paper cites DP-NCB: Privacy Preserving Fair Bandits.

Improved Algorithms for Nash Welfare in Linear Bandits DP-NCB: Privacy Preserving Fair Bandits

Reference 2013

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:51.599150Z digest=sha256:d4bc19c4a3ea7d7278fe722d8f4c4c461a50e03df6141da316a07bab83ceeef5

Observation 921cc236-1836-41a9-812b-925d11ed5197 · outbound

This paper cites an unresolved cited work.

Improved Algorithms for Nash Welfare in Linear Bandits Unresolved cited work

Reference 2016

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:28:51.654531Z digest=sha256:e2cff955b2065b95ded431cde7972fe8c47da942ad5b3fcb368dd9cfe2027b81

Pith citing papers

No inbound Pith citation observations are available.