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Paper Citation Record · LEDGER

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation

As of 10 August 2026, this Paper Citation Record lists 100 of 299 outbound references and 0 inbound Pith citation observations for arXiv:2608.04333.

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

pith.paper-citation-record.v1
2608.04333 v1

Coverage vector

measured 100 of 299 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:48:09.296553Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

100 of 299 outbound references displayed

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  • verified fuzzy0
  • unresolved100
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 8fd31253-84fc-473d-8f92-0820b40b7ef7 · outbound

This paper cites Proceedings of the 29th International Joint Conference on Artificial Intelligence , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 29th International Joint Conference on Artificial Intelligence , pages =

Reference 1

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source=arxiv_source observed=2026-08-08T19:48:08.798882Z digest=sha256:1dcd79041e07bf374481727f86ab7e83714a6eba2fe56b7845044b41376b5e5b

Observation 0972ff51-7be1-487c-8a16-2764c24ce67a · outbound

This paper cites Traversing Pareto Optimal Policies: Provably Efficient Multi-Objective Reinforcement Learning.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Traversing Pareto Optimal Policies: Provably Efficient Multi-Objective Reinforcement Learning

Reference 2

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source=arxiv_source observed=2026-08-08T19:48:08.805698Z digest=sha256:f67cc14e686f72ce48f42b39640c125cf110ccd63e91176c59f0decd744f53a3

Observation 5cc2d915-5b29-4add-949c-91b3d05a69be · outbound

This paper cites Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Efficient Algorithms for Generalized Linear Bandits with Heavy-tailed Rewards , year =

Reference 3

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source=arxiv_source observed=2026-08-08T19:48:08.811549Z digest=sha256:035f9897efab874561992a9b0d0e9817c5a7f6d976c1ab43a0cedfab24a41b95

Observation 96e38da2-39b3-42a5-ae28-5bc7ebf9234c · outbound

This paper cites Multiobjective Lipschitz Bandits under Lexicographic Ordering , journal=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Multiobjective Lipschitz Bandits under Lexicographic Ordering , journal=

Reference 4

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source=arxiv_source observed=2026-08-08T19:48:08.816693Z digest=sha256:4fae5c4245b44d6f6f1cb9563ca8b6cccbc1ab21fe1631fa3c01eb482adf8dc0

Observation e2f8a7ac-b4ff-4111-bf89-28c79e7d4e26 · outbound

This paper cites Proceedings of the 34th International Joint Conference on Artificial Intelligence , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 34th International Joint Conference on Artificial Intelligence , pages =

Reference 5

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source=arxiv_source observed=2026-08-08T19:48:08.824000Z digest=sha256:f6df45f109a70dceb2887aaffb31eb7eaaaeb3044dabf4f65d9cc41203b4039f

Observation d1ada696-825f-46ca-bfbf-79a432547e14 · outbound

This paper cites Multiple Trade-offs: An Improved Approach for Lexicographic Linear Bandits , booktitle=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Multiple Trade-offs: An Improved Approach for Lexicographic Linear Bandits , booktitle=

Reference 6

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source=arxiv_source observed=2026-08-08T19:48:08.829437Z digest=sha256:e144f129c4c13954b001857e2faf505b11f4be43da4fa01b47b587f821a64ab1

Observation be175778-a7d1-4b1e-a84a-16d029d8fd1f · outbound

This paper cites Proceedings of the 42nd International Conference on Machine Learning , year=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 42nd International Conference on Machine Learning , year=

Reference 7

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source=arxiv_source observed=2026-08-08T19:48:08.835089Z digest=sha256:9ead1707adfc2d0b38c26b4d108a89aa0c621a148f26a9f0d8b2386ac0e496ce

Observation 7d479bde-30ad-4b21-bacd-6f39175f44ac · outbound

This paper cites Hierarchize Pareto Dominance in Multi-Objective Stochastic Linear Bandits , booktitle=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Hierarchize Pareto Dominance in Multi-Objective Stochastic Linear Bandits , booktitle=

Reference 8

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source=arxiv_source observed=2026-08-08T19:48:08.840139Z digest=sha256:50cc65c815ac51f2d51ba412cc6ec3c05619ee7db1239c5c9d5c16a193debf73

Observation e4a217ff-e05b-41f1-a3ed-0c035faeaff4 · outbound

This paper cites Proceedings of the 34th International Joint Conference on Artificial Intelligence , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 34th International Joint Conference on Artificial Intelligence , pages =

Reference 9

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source=arxiv_source observed=2026-08-08T19:48:08.845037Z digest=sha256:1145eb9454e0ed8b89d3aef6fb2fe73cd83f0392340896f4abe1cf0fea313f09

Observation ae913ee5-f0a0-4cea-afca-260366996887 · outbound

This paper cites Using Confidence Bounds for Exploitation-Exploration Trade-offs , journal =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Using Confidence Bounds for Exploitation-Exploration Trade-offs , journal =

Reference 10

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source=arxiv_source observed=2026-08-08T19:48:08.849784Z digest=sha256:0597c3d5ee38c9b308abfbfa96665351dbdf72134be4a0c71c0820670a081b37

Observation e173c691-b86f-48ae-baf9-f45bf32fd3ef · outbound

This paper cites Bandits With Heavy Tail , year=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Bandits With Heavy Tail , year=

Reference 11

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source=arxiv_source observed=2026-08-08T19:48:08.854423Z digest=sha256:ec2e96c20660896c661181fd97838c2c961f6b49a30c46f124506caac2bbfbd7

Observation e037ce4c-d0c8-4360-b33c-8aa8bfb2f97f · outbound

This paper cites Weighted sums of certain dependent random variables.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Weighted sums of certain dependent random variables

Reference 12

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source=arxiv_source observed=2026-08-08T19:48:08.859439Z digest=sha256:c9604087f35d17fcb7925ec86798d856ac7abb5e6afc08a2e7b661a04157e527

Observation ecff11a6-ba36-4f8d-8cf3-6fa7ea1f74d8 · outbound

This paper cites Annales de l'I.H.P.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Annales de l'I.H.P

Reference 13

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source=arxiv_source observed=2026-08-08T19:48:08.864172Z digest=sha256:1eb1d6c5385df0f19c8c29bac7b5d82c3ffb2b7af9602656a0d7fc158eb6996e

Observation a11ac636-5b7c-4b43-a0cf-d21579cdca2f · outbound

This paper cites Some aspects of the sequential design of experiments.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Some aspects of the sequential design of experiments

Reference 14

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source=arxiv_source observed=2026-08-08T19:48:08.868886Z digest=sha256:3d485e38b917b6adb1d80bbafa92172ead3073d2bd556f241e69a610ea7b6ca0

Observation 10c2399e-ba78-47a0-bbde-412dfedde4db · outbound

This paper cites and Long, Philip M.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation and Long, Philip M

Reference 15

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source=arxiv_source observed=2026-08-08T19:48:08.874249Z digest=sha256:f6423dc25e51c1cd7d9afd8ac0bf7e2fbb4f58763958748bb1967fa62e73a325

Observation daf2462c-8e92-465c-83fe-ab97d46d0383 · outbound

This paper cites The heavy tail of the human brain.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation The heavy tail of the human brain

Reference 16

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source=arxiv_source observed=2026-08-08T19:48:08.879109Z digest=sha256:dfaafe83c62088c66eff26fa460b8d2a074455ce50a89c747825c1ecd462db7b

Observation c044e3b1-c075-4849-ae86-d9a0b2daa773 · outbound

This paper cites , title =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation , title =

Reference 17

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source=arxiv_source observed=2026-08-08T19:48:08.883824Z digest=sha256:672a7cf8c0018efcee25897b427a9c9b9909af55709c295d2bafd790df339df7

Observation f0763115-c79d-4fe5-ba97-0649cc33ec65 · outbound

This paper cites Proceedings of the 33rd International Conference on International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 33rd International Conference on International Conference on Machine Learning , pages =

Reference 18

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source=arxiv_source observed=2026-08-08T19:48:08.888384Z digest=sha256:ce2a491d4f5a7cbc4dd05a25eb31a37b0adbbe636acd9fbc621717bf9d7647fa

Observation ea692851-e741-4834-879a-cff1728b03db · outbound

This paper cites Proceedings of the 14th International Conference on Artificial Intelligence and Statistics , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 14th International Conference on Artificial Intelligence and Statistics , pages =

Reference 19

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source=arxiv_source observed=2026-08-08T19:48:08.892873Z digest=sha256:0db29c136c5e4d00d2eab23695ef7f16792e94708926bcb6aef7c9efea5bd5ca

Observation 8394fde3-392f-410c-aaf5-2cda74aa91de · outbound

This paper cites Proceedings of the 31st International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 31st International Conference on Machine Learning , pages =

Reference 20

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source=arxiv_source observed=2026-08-08T19:48:08.897722Z digest=sha256:0c66ced5269a180f15924018f7650090791d9d161fff2d17892c011ab9738351

Observation 661aa7dd-be3e-493f-a6d5-54ad0ef33935 · outbound

This paper cites Proceedings of the 31st Conference On Learning Theory , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 31st Conference On Learning Theory , pages =

Reference 21

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Observation eddf89e6-4711-4c34-a1cc-2b1ce924a557 · outbound

This paper cites Proceedings of the 31st International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 31st International Conference on Machine Learning , pages =

Reference 22

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source=arxiv_source observed=2026-08-08T19:48:08.907418Z digest=sha256:414169cd9de94b22b6ba1f5aad64cbb665604a9cc055181724d4bcc05a49e40d

Observation 55817c24-8d11-41ae-b279-617698bdd8c5 · outbound

This paper cites _1 -regression with Heavy-tailed Distributions , booktitle =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation _1 -regression with Heavy-tailed Distributions , booktitle =

Reference 23

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source=arxiv_source observed=2026-08-08T19:48:08.912080Z digest=sha256:d41532ea370554ca1ef08f1e897e147c3f7c394e3914f189fd40dd092e207f54

Observation 82c5d418-6ddc-496e-a19d-a6a7cca35d83 · outbound

This paper cites Online Stochastic Linear Optimization under One-bit Feedback , booktitle =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Online Stochastic Linear Optimization under One-bit Feedback , booktitle =

Reference 24

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Observation b237581d-4212-4108-a2b6-ce015eb48c2a · outbound

This paper cites , title =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation , title =

Reference 25

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source=arxiv_source observed=2026-08-08T19:48:08.922801Z digest=sha256:f3f60036c65d55fd7de8060babf56bc79be6f533354af69d99ee69b7bad4c0e1

Observation c984b065-0d5d-4bb4-9d06-8555c187034a · outbound

This paper cites Advances in Neural Information Processing Systems 24 , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Advances in Neural Information Processing Systems 24 , pages =

Reference 26

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source=arxiv_source observed=2026-08-08T19:48:08.927266Z digest=sha256:ecc396566ae8ee239aad7df29a72861d93579339eef432432edcca20b35d40d7

Observation 6e987f98-ef34-4a9a-a9ce-fa9c0b9b57e8 · outbound

This paper cites Proceedings of the 15th International Conference on Artificial Intelligence and Statistics , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 15th International Conference on Artificial Intelligence and Statistics , pages =

Reference 27

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source=arxiv_source observed=2026-08-08T19:48:08.932170Z digest=sha256:b8fad99c84513b4e2a61c2bfa7411f1ff30c5b86c5b011ca9ca20084d15813ad

Observation 0382bf69-64e3-4fa8-a173-cb2c993c3f34 · outbound

This paper cites Advances in Neural Information Processing Systems 24 , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Advances in Neural Information Processing Systems 24 , pages =

Reference 28

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source=arxiv_source observed=2026-08-08T19:48:08.937404Z digest=sha256:d40bb4b994d7ee9a26dc98b8c87f818ba29d37d8f0d291ecc46d0a62f81a0ef2

Observation df521b00-8e82-4e67-bf22-860fd38554de · outbound

This paper cites an unresolved cited work.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Unresolved cited work

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source=arxiv_source observed=2026-08-08T19:48:08.942294Z digest=sha256:f7f14ae08d3d2979d3f2c70c4861f844f41aa795ea60bb553f423f23c4736f5e

Observation 3a56df90-ad34-4996-b3de-0e64fee199e7 · outbound

This paper cites Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems , JOURNAL =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems , JOURNAL =

Reference 30

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source=arxiv_source observed=2026-08-08T19:48:08.947323Z digest=sha256:e549d1cf5377b540eb3b92d865df5d9668e4d9b8499a4b482c95cf0139b276fd

Observation e438c4f9-6830-4647-a808-7a2f94e665b2 · outbound

This paper cites Asymptotically efficient adaptive allocation rules.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Asymptotically efficient adaptive allocation rules

Reference 31

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Observation ad5e6d71-27e3-4243-b0be-9a980ac0c2a2 · outbound

This paper cites Proceedings of the 23rd Annual Conference on Learning Theory , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 23rd Annual Conference on Learning Theory , pages =

Reference 32

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source=arxiv_source observed=2026-08-08T19:48:08.958214Z digest=sha256:8f178348df232d69809245ff8103a36934664fb82cae3e752a0c4ed50ac651e4

Observation 42fddafd-113c-41cf-9b84-acaf6fe5f492 · outbound

This paper cites Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Best Arm Identification: A Unified Approach to Fixed Budget and Fixed Confidence , year =

Reference 33

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source=arxiv_source observed=2026-08-08T19:48:08.963635Z digest=sha256:da0e3aeb6e8f5bb82f31c11cf6194f55b91cf5360b9816395977450bb13fa4c4

Observation 43dc4676-a4e7-4e42-bc85-e858292afccf · outbound

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Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Unresolved cited work

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source=arxiv_source observed=2026-08-08T19:48:08.968806Z digest=sha256:fc99c5eb62872d4b31916980d07dab3bb24279b382805fef95201b149112358a

Observation 8f497461-d87f-4057-b91c-65e18fbfe105 · outbound

This paper cites and Kalai, Adam Tauman and McMahan, H.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation and Kalai, Adam Tauman and McMahan, H

Reference 35

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source=arxiv_source observed=2026-08-08T19:48:08.974477Z digest=sha256:bb6e450564ec8eb2f91481c22d32361ec9eba8c1de054331975f97b3dc56577f

Observation adb35ac1-2a41-4033-9ff0-ceb527e4fbe7 · outbound

This paper cites Proceedings of the 40th Annual ACM Symposium on Theory of Computing , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 40th Annual ACM Symposium on Theory of Computing , year =

Reference 36

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Observation 641e416c-77da-41e5-9341-fa199eb7ebac · outbound

This paper cites Advances in Applied Probability , YEAR =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Advances in Applied Probability , YEAR =

Reference 37

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source=arxiv_source observed=2026-08-08T19:48:08.984846Z digest=sha256:529daba81a43cd1d765f0512455ff72edfcb66c9100f9f5dbbdf0ac0e6a01390

Observation 0d596b5e-8f0d-45da-a325-a367ec681f4a · outbound

This paper cites Finite-time Analysis of the Multiarmed Bandit Problem , journal =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Finite-time Analysis of the Multiarmed Bandit Problem , journal =

Reference 38

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source=arxiv_source observed=2026-08-08T19:48:08.990548Z digest=sha256:b6210792fcc569c09582918a141c12378b275cad87647c601c55de4a6d93c490

Observation 36c47f79-0c6a-4dd3-b60d-26b098890a04 · outbound

This paper cites IEEE Journal of Selected Topics in Signal Processing , pages=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation IEEE Journal of Selected Topics in Signal Processing , pages=

Reference 39

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source=arxiv_source observed=2026-08-08T19:48:08.996843Z digest=sha256:ddb98ea5620dfd2d76bda6918ef3257df73b2da560cc4ab04c0f8172d101a7b9

Observation 91534c6c-4594-450c-804d-9a1fb5feea2a · outbound

This paper cites Hayes and Sham M.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Hayes and Sham M

Reference 40

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source=arxiv_source observed=2026-08-08T19:48:09.002042Z digest=sha256:52ebd03097346c2630aabce9b04b22b073bd78a1a8b8f80cdfe9e5cef1f16f7b

Observation 48c7d30f-a78e-476d-baed-18abb4b337ca · outbound

This paper cites The Nonstochastic Multiarmed Bandit Problem , journal =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation The Nonstochastic Multiarmed Bandit Problem , journal =

Reference 41

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source=arxiv_source observed=2026-08-08T19:48:09.007159Z digest=sha256:c776529655d38f64b60916e460df15aef504b136472aab16c265360f787720ea

Observation ebd98e8c-4886-4826-b56d-2c1adb6a4700 · outbound

This paper cites and Thomas, Joy A.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation and Thomas, Joy A

Reference 42

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source=arxiv_source observed=2026-08-08T19:48:09.012924Z digest=sha256:b08c0deed9c8faa31d86fe4beb622044ba1e45396511b19945bc4b5da22022cd

Observation 3fb2e00e-7a17-4055-a322-c125629feaab · outbound

This paper cites IEEE Transactions on Information Theory , volume=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation IEEE Transactions on Information Theory , volume=

Reference 43

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source=arxiv_source observed=2026-08-08T19:48:09.018434Z digest=sha256:efc1b1ba8e7233a6c5392d045b0961bbb8b848048c0a39c6cdc9fd2f1a4824df

Observation f82f4041-c246-4c9f-9f71-e24c7053945c · outbound

This paper cites Robust linear least squares regression.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Robust linear least squares regression

Reference 44

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source=arxiv_source observed=2026-08-08T19:48:09.023109Z digest=sha256:9b40e5d208917e5cfa22b54899eb7134d8574fac4389d973644209f708979d9a

Observation afe48405-f7a0-48d8-a331-0bb238aa560b · outbound

This paper cites Empirical risk minimization for heavy-tailed losses.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Empirical risk minimization for heavy-tailed losses

Reference 45

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source=arxiv_source observed=2026-08-08T19:48:09.028576Z digest=sha256:309dba18a904c1e2a61adbdac5248c7bc2d9cf943a9a90c54ed79952148a1037

Observation 4e30f7b3-65cf-4b95-82a4-4f290509911e · outbound

This paper cites Journal of Machine Learning Research , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Journal of Machine Learning Research , year =

Reference 46

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source=arxiv_source observed=2026-08-08T19:48:09.035972Z digest=sha256:c4bd79b445bf6c4264f15b39d22b3b60d311f4fdffec224e4c26c48783ae4740

Observation 9979b6ea-3c5e-44fa-9543-1d4e8885a5cd · outbound

This paper cites Proceedings of the 36th International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 36th International Conference on Machine Learning , pages =

Reference 47

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source=arxiv_source observed=2026-08-08T19:48:09.040814Z digest=sha256:ed2494884a30da39ae004f40f59e3312af8f6c67bfc70f873345011b8abf4870

Observation 9939ebf8-939e-40d8-ab19-b02e4e32d961 · outbound

This paper cites and Van Loan,, Charles F.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation and Van Loan,, Charles F

Reference 48

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source=arxiv_source observed=2026-08-08T19:48:09.046078Z digest=sha256:59d91953e111e518baa99600caf92a6aa8e05cd02e6a0d023672a18759343ff0

Observation d7753eca-322c-4954-b416-23b8aac6a8be · outbound

This paper cites and Hsu, Daniel and Kakade, Sham M.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation and Hsu, Daniel and Kakade, Sham M

Reference 49

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source=arxiv_source observed=2026-08-08T19:48:09.051104Z digest=sha256:be3767d68a5fffec64a0e9fcdd97934be68a518a1b522c025a71c7ba175e6837

Observation aafde88d-a3fd-4468-bf4c-ccc06d59df82 · outbound

This paper cites 2014 , journal =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation 2014 , journal =

Reference 50

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source=arxiv_source observed=2026-08-08T19:48:09.055708Z digest=sha256:aadf54981b60b4e7197afb40465af7e0f79f1683cd9905389a28025efe5afb7a

Observation fc0f7d2c-507f-4e81-aa77-c26283af6fad · outbound

This paper cites Lyu and Irwin King , title =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Lyu and Irwin King , title =

Reference 51

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source=arxiv_source observed=2026-08-08T19:48:09.060323Z digest=sha256:0459bab98d8e29a47bc40ae75c85fa9577844403279c96e5406b6aee46d2f4a3

Observation ca386da2-0cf9-4061-9752-14363ffe5284 · outbound

This paper cites Lipschitz Bandits Without the Lipschitz Constant , booktitle =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Lipschitz Bandits Without the Lipschitz Constant , booktitle =

Reference 52

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source=arxiv_source observed=2026-08-08T19:48:09.064946Z digest=sha256:6b1ed5ec4b1aa199c375ac260916e1a90ecbc0cb93a2b0035303fef3dd5c13ca

Observation dee84585-1a34-4400-bb04-0be85934d1bb · outbound

This paper cites SIAM Journal on Control and Optimization , volume =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation SIAM Journal on Control and Optimization , volume =

Reference 53

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source=arxiv_source observed=2026-08-08T19:48:09.069564Z digest=sha256:ff268f5677417d1d757653f2853ec4f0197349db5a5a9a024724caec798c8613

Observation 1bc617cf-41d8-479b-aa3e-29c43f8e9ce7 · outbound

This paper cites Bandit Convex Optimization:.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Bandit Convex Optimization:

Reference 54

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source=arxiv_source observed=2026-08-08T19:48:09.074163Z digest=sha256:e977ab5f5e1e79b871ef5f986e01025b15fe8446e9492aafcec966baf8e6fc03

Observation f940fc76-478b-4402-bdf9-35f7e7ac2086 · outbound

This paper cites Bandit Algorithms , publisher=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Bandit Algorithms , publisher=

Reference 55

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source=arxiv_source observed=2026-08-08T19:48:09.078705Z digest=sha256:9204a055670930910f0c39119d2fff6617b4335fdf790844fb5a69fc410dacef

Observation e4edf2bb-7d2f-4a24-96d0-311c5b2d0a93 · outbound

This paper cites Advances in Neural Information Processing Systems 23 , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Advances in Neural Information Processing Systems 23 , pages =

Reference 56

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source=arxiv_source observed=2026-08-08T19:48:09.083321Z digest=sha256:499887db03b94f059f5651aefa720c10e30982483b4c52307fe0b490095f99cc

Observation 6cba610f-9815-4595-a245-4aa15512a633 · outbound

This paper cites Advances in Neural Information Processing Systems 30 , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Advances in Neural Information Processing Systems 30 , pages =

Reference 57

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source=arxiv_source observed=2026-08-08T19:48:09.088263Z digest=sha256:28a5b907d650b007de105e4cd4af406aa8a8098abedd8fef348e40a50b115a49

Observation f5d969d0-6ab8-435c-8853-7e17a5453226 · outbound

This paper cites McCullagh, John A.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation McCullagh, John A

Reference 58

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source=arxiv_source observed=2026-08-08T19:48:09.093422Z digest=sha256:b785e9248c6505a7ae695f9f04824da2ad6dac8d045aeddc12b65e8ec3e1bcf5

Observation 94baa971-e410-4dc2-ac48-b72b9644fe23 · outbound

This paper cites Hubert and Shi, Elaine and Song, Dawn , title =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Hubert and Shi, Elaine and Song, Dawn , title =

Reference 59

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source=arxiv_source observed=2026-08-08T19:48:09.098537Z digest=sha256:14ae6eb07362c7fa2c60a3160815338713b5b306e4ab2a05e130729dfcba43f4

Observation 861c5329-df4d-4c9f-9b0d-afadd4806bbd · outbound

This paper cites Proceedings of the 28th International Joint Conference on Artificial Intelligence , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 28th International Joint Conference on Artificial Intelligence , pages =

Reference 60

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source=arxiv_source observed=2026-08-08T19:48:09.103641Z digest=sha256:a9b9af90bf741a2bb9c5345045bb5281c8510a85ba5dacb806299f7939a305fd

Observation 282cd500-dde9-4974-b484-f6904d7d0dfb · outbound

This paper cites Logarithmic Regret Algorithms for Online Convex Optimization , journal =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Logarithmic Regret Algorithms for Online Convex Optimization , journal =

Reference 61

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source=arxiv_source observed=2026-08-08T19:48:09.108305Z digest=sha256:71bf2bd4a581c29660a70041ab4efc04490f89628977acb4ddde982f1dd17ed1

Observation c5d5fc10-cbc4-4f2e-8cdb-913dc9287f0c · outbound

This paper cites Proceedings of the 34th International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 34th International Conference on Machine Learning , pages =

Reference 62

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source=arxiv_source observed=2026-08-08T19:48:09.113150Z digest=sha256:da5946fa433f5511f39a99c64e430959294d259c9f6bd5da5e0f716150457363

Observation 5f94923a-7b55-4330-932e-27a17e89a726 · outbound

This paper cites Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs , year =

Reference 63

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source=arxiv_source observed=2026-08-08T19:48:09.117927Z digest=sha256:317b72a72aa799ed9e8ed6a62ef63dd486b9fe81120cfdab8c2314146ae4febd

Observation 178f0649-ff79-4c23-b55d-83f24d3d140b · outbound

This paper cites The Annals of Statistics , number =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation The Annals of Statistics , number =

Reference 64

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source=arxiv_source observed=2026-08-08T19:48:09.123261Z digest=sha256:594922c19626243a6263c7848b802581f14502976cbc309af247009d83b7cf8b

Observation 945dbf76-d3a7-4e22-9881-9a9359bd7655 · outbound

This paper cites Bayesian Optimization under Heavy-tailed Payoffs , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Bayesian Optimization under Heavy-tailed Payoffs , year =

Reference 65

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source=arxiv_source observed=2026-08-08T19:48:09.128018Z digest=sha256:3a64cef2a6033ef1cb0b0d7b6065b894b5dee95bf84c080019da4c5021d69110

Observation 80865a51-a96f-4b3b-907f-5cdb54164705 · outbound

This paper cites IEEE transactions on pattern analysis and machine intelligence , pages=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation IEEE transactions on pattern analysis and machine intelligence , pages=

Reference 66

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source=arxiv_source observed=2026-08-08T19:48:09.132770Z digest=sha256:6b326d3c155cbab2a16611ab8ec6198e3f8dac09a33a2f5796934f5a817f79b3

Observation 6f221714-719a-403d-8623-d603bffba240 · outbound

This paper cites Proceedings of the 29th International Joint Conference on Artificial Intelligence , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 29th International Joint Conference on Artificial Intelligence , year =

Reference 67

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source=arxiv_source observed=2026-08-08T19:48:09.137503Z digest=sha256:b318afc2f1a2e431d8e8e9fea1b50258c4ff8fead85f9ea8bd26c390f8152105

Observation 437e0814-91ac-48fe-a9ca-5ab6a27941aa · outbound

This paper cites and Nowe, Ann , booktitle=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation and Nowe, Ann , booktitle=

Reference 68

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source=arxiv_source observed=2026-08-08T19:48:09.142279Z digest=sha256:c15a85c97627e5e71a63d2ba429fff0ea9d3a1d3f0e6ee3f6b9b1023adef25a9

Observation ed20b312-0716-4aaf-b770-d20e4e4dafc6 · outbound

This paper cites Proceedings of the 19th International Conference on Artificial Intelligence and Statistics , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 19th International Conference on Artificial Intelligence and Statistics , pages =

Reference 69

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source=arxiv_source observed=2026-08-08T19:48:09.146852Z digest=sha256:12c285fad7dd1305a4ba20f59c9147bf58ce436ac129e52bd3be3463160a14db

Observation 64a890a0-cffc-4c03-8f27-d29a62e6f3c3 · outbound

This paper cites 2005 , publisher =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation 2005 , publisher =

Reference 70

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source=arxiv_source observed=2026-08-08T19:48:09.151288Z digest=sha256:a56f2ba3faa8b3f0aa7613dec380a0dd13d0ecadd3ddbf2bca4eb8bb05043301

Observation 395a43b2-2f1d-4647-ac9d-1ee00c357dd6 · outbound

This paper cites Multi-objective multi-armed bandit with lexicographically ordered and satisficing objectives , journal =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Multi-objective multi-armed bandit with lexicographically ordered and satisficing objectives , journal =

Reference 71

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source=arxiv_source observed=2026-08-08T19:48:09.156255Z digest=sha256:58d624050bfabd2c30812f94eccf877b58a2a8fc48a38a815cce2f42c19f25cd

Observation ef4b028a-ce30-4902-a3a4-9fdfded65eff · outbound

This paper cites Proceedings of the 21st International Conference on Artificial Intelligence and Statistics , pages=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 21st International Conference on Artificial Intelligence and Statistics , pages=

Reference 72

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source=arxiv_source observed=2026-08-08T19:48:09.161400Z digest=sha256:cfb3c3482cdc03844882e82794061d56882bcb500720aa84c41b0335e17e7a66

Observation 4a07494b-ae1b-4c2a-8834-b94d1a14d0e1 · outbound

This paper cites Multi-objective.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Multi-objective

Reference 73

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source=arxiv_source observed=2026-08-08T19:48:09.166211Z digest=sha256:7f73724e739685f1a597e080dd6b4152135898332b082571f8c452493dea536b

Observation 55737148-7049-481a-b2da-9dbc3bcc23f9 · outbound

This paper cites Proceedings of the 39th International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 39th International Conference on Machine Learning , pages =

Reference 74

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source=arxiv_source observed=2026-08-08T19:48:09.170898Z digest=sha256:42801dcce43460b69255a020b12adefca17cc9652cd9dad7e4c45d968f3a437d

Observation 945fcc69-9a13-41d3-9afb-c5e69cc9ebbb · outbound

This paper cites 2016 , booktitle =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation 2016 , booktitle =

Reference 75

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source=arxiv_source observed=2026-08-08T19:48:09.175584Z digest=sha256:eb2a9b11d1b9da6334d186a5a9e56a39544dc7bf93dc79e587a396c12684471e

Observation bad33a7b-757b-4539-a58a-58a9c78917d3 · outbound

This paper cites 2012 , booktitle =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation 2012 , booktitle =

Reference 76

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source=arxiv_source observed=2026-08-08T19:48:09.180059Z digest=sha256:a5bca23a2fb32d5efdbc91a5b4e3dd1889242fc1c987bbc026ffd0ac24640ffe

Observation a62e4eb0-f17e-44e0-8c45-eac5f2386add · outbound

This paper cites 2004 , publisher=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation 2004 , publisher=

Reference 77

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source=arxiv_source observed=2026-08-08T19:48:09.184587Z digest=sha256:53e38b4cc3b313e0c7f5e25c0cc70cfc7a1455496a0c6056902ab5ead7e1854a

Observation 1e697ab4-94c3-4ad5-a290-1a4d5dbad685 · outbound

This paper cites Breaking the.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Breaking the

Reference 78

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source=arxiv_source observed=2026-08-08T19:48:09.189668Z digest=sha256:c38281e4786674ca897b5d73dc823c73779db767cc339b55c55c1741e256fcfe

Observation 676fed44-ef5a-4247-8f1f-de5e85c569b0 · outbound

This paper cites Proceedings of the 39th International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 39th International Conference on Machine Learning , pages =

Reference 79

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source=arxiv_source observed=2026-08-08T19:48:09.194334Z digest=sha256:41dfed82af4fbfaf7512432ae5b7faff018f1b5ce1ea68cf4a363395a1fdaaaf

Observation 4f710852-c899-41fc-9d4b-98a59366182c · outbound

This paper cites Proceedings of the 39th International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 39th International Conference on Machine Learning , pages =

Reference 80

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source=arxiv_source observed=2026-08-08T19:48:09.199360Z digest=sha256:f5e50fb1d107e6bdeaee8f2d9a0b122f782ac43f2d433dc7ac3a54c8f59ae403

Observation d03e01b1-dfdb-439f-93a9-c94c859a93df · outbound

This paper cites Proceedings of the 39th International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 39th International Conference on Machine Learning , pages =

Reference 81

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source=arxiv_source observed=2026-08-08T19:48:09.204282Z digest=sha256:3f7086936d413ad0f64a95572d2121cc189e38d9c6bbabd8348094ed37af5f7a

Observation 5868ad39-d161-40b8-8c83-6b3c24b67c02 · outbound

This paper cites Proceedings of the 39th International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 39th International Conference on Machine Learning , pages =

Reference 82

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source=arxiv_source observed=2026-08-08T19:48:09.209046Z digest=sha256:540b530248201c89ce961d29a9c4d487d7006d4efdb5e466d05ab2bb72f795ed

Observation ada68993-93c1-4f1d-b9d7-2934b536acd4 · outbound

This paper cites A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation A Best-of-Both-Worlds Algorithm for Bandits with Delayed Feedback , year =

Reference 83

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source=arxiv_source observed=2026-08-08T19:48:09.214454Z digest=sha256:c887d52cfa715e75ffbc017cc14e190a167ee4c61b12d36c9addfab059396ec7

Observation a3b3642a-326e-4a86-9317-719fc9841ec3 · outbound

This paper cites Lipschitz Bandits with Batched Feedback , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Lipschitz Bandits with Batched Feedback , year =

Reference 84

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source=arxiv_source observed=2026-08-08T19:48:09.220001Z digest=sha256:f06b096a7b70c1a63e3a8546b5a664309fbff9995c9622cc1d82c9faf58d37e0

Observation 48b835a9-49c6-4173-91b4-dc79a69f1181 · outbound

This paper cites Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Finite-Time Regret of Thompson Sampling Algorithms for Exponential Family Multi-Armed Bandits , year =

Reference 85

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source=arxiv_source observed=2026-08-08T19:48:09.225272Z digest=sha256:199bd5ca29b8268a067ec77f871ee8e558e4234ca88197cd3f550347f0d2e211

Observation 79dcba4a-49a2-46db-b94e-20107090db36 · outbound

This paper cites Communication Efficient Federated Learning for Generalized Linear Bandits , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Communication Efficient Federated Learning for Generalized Linear Bandits , year =

Reference 86

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source=arxiv_source observed=2026-08-08T19:48:09.230075Z digest=sha256:70796da49849f66dfdba8fc026e8419447a61a6060088714e823681e7d30ae34

Observation a2cfeaa5-1dff-400f-8bf1-147f2438febf · outbound

This paper cites Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions , year =

Reference 87

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source=arxiv_source observed=2026-08-08T19:48:09.235115Z digest=sha256:b4be1e2480de5aaa85bbbe518b6dfb0d2ed3cb4221c0dd02bf13edfb68c65605

Observation 4ad366c7-33b0-4a48-848c-e70f487d97a6 · outbound

This paper cites Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise , year =

Reference 88

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source=arxiv_source observed=2026-08-08T19:48:09.240079Z digest=sha256:8695c44895e66631dc9b423e5168d7d1839c8392e68fa9135d68c3c6b093f13e

Observation 1a5bfa4a-d334-4859-8556-32411fa1ad69 · outbound

This paper cites Proceedings of the 39th International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 39th International Conference on Machine Learning , pages =

Reference 89

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source=arxiv_source observed=2026-08-08T19:48:09.244774Z digest=sha256:8ceaef3a9547d9799107eb4e0a86bc7bda9d7e0c9c9c34d9bf038a29e84fb689

Observation 8fa39087-c1e5-423e-9ab3-47e3649240cc · outbound

This paper cites Proceedings of the 39th International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 39th International Conference on Machine Learning , pages =

Reference 90

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source=arxiv_source observed=2026-08-08T19:48:09.249498Z digest=sha256:6d18e1a41a3035f994fa6edd0ed7cb35a742d511b0dffb15c4a70bb1eb6dbd7c

Observation cb65bf20-4da8-4f58-9464-a2c7b9a87d87 · outbound

This paper cites Multi-armed Bandit Models for the Optimal Design of Clinical Trials: Benefits and Challenges , volume =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Multi-armed Bandit Models for the Optimal Design of Clinical Trials: Benefits and Challenges , volume =

Reference 91

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source=arxiv_source observed=2026-08-08T19:48:09.253967Z digest=sha256:eced950df13dd584eb55eb4b174edcb7437d38bef882f43a1cf30882c3f91781

Observation 69f8f945-d901-47f0-b3a7-d409adc40da8 · outbound

This paper cites MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , year=.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition , year=

Reference 92

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source=arxiv_source observed=2026-08-08T19:48:09.258843Z digest=sha256:cdaf3f84caa87f2dd240e478ad21724023823834f66cb7312d6b93314f231631

Observation 8fa622b0-56a8-49a8-81dc-6932cd246bef · outbound

This paper cites Proceedings of the 38th International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 38th International Conference on Machine Learning , pages =

Reference 93

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source=arxiv_source observed=2026-08-08T19:48:09.263707Z digest=sha256:ba2d9ec340d0f1f6a31306367dc490927db535a9f1d96e3ac6c452d1e6ee3441

Observation d5ec6375-d282-41a0-ba6d-9fbd24149041 · outbound

This paper cites Proceedings of the 38th International Conference on Machine Learning , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 38th International Conference on Machine Learning , pages =

Reference 94

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source=arxiv_source observed=2026-08-08T19:48:09.268629Z digest=sha256:c8550929ef7957b292cdc07b93c841527000d3127b4283dcb55866bb014f537d

Observation 13dcc6b8-3641-4a40-84b7-651023ffe422 · outbound

This paper cites 2012 , volume =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation 2012 , volume =

Reference 95

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source=arxiv_source observed=2026-08-08T19:48:09.273188Z digest=sha256:9f660888d44aa4b951b8d7a0d0d3355d4815fb99f4982530693d6480a2f8e74c

Observation 911145b7-bd64-4199-96e1-15586aca7bd0 · outbound

This paper cites and Barto, Andrew G.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation and Barto, Andrew G

Reference 96

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source=arxiv_source observed=2026-08-08T19:48:09.278149Z digest=sha256:074a25422248950753d3f29bff97a6efeab226a9d13b67347ace99c003df8dec

Observation dcc7f4c5-58cd-4d07-8d46-09034e9ea75a · outbound

This paper cites Proceedings of the 24th International Conference on Artificial Intelligence and Statistics , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Proceedings of the 24th International Conference on Artificial Intelligence and Statistics , pages =

Reference 97

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source=arxiv_source observed=2026-08-08T19:48:09.282824Z digest=sha256:d7e49a657358595e39ab3d10fd5f363e63efabc6e1510ce0cbac592ab66bf021

Observation 6d6a0020-4663-44d7-801b-50e488f8f132 · outbound

This paper cites PAC-Bayesian Inequalities for Martingales , journal =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation PAC-Bayesian Inequalities for Martingales , journal =

Reference 98

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source=arxiv_source observed=2026-08-08T19:48:09.287161Z digest=sha256:4412d8cda09e7ffb9fbf9ea756ac0cd971c1a6c3e0b56b9941892c42be98fbb5

Observation c17c1cc6-abb6-43d3-aea8-ead96d808650 · outbound

This paper cites Learning in Generalized Linear Contextual Bandits with Stochastic Delays , year =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Learning in Generalized Linear Contextual Bandits with Stochastic Delays , year =

Reference 99

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source=arxiv_source observed=2026-08-08T19:48:09.291880Z digest=sha256:2bcbc10d00cb670599bced6abe0f2680b0304516d5ace0f8114610fc5931034e

Observation 4e1415ac-e24d-43d9-ad5a-267e94d1d8b3 · outbound

This paper cites Advances in Neural Information Processing Systems 34 , pages =.

Cost-Aware Multi-Objective Bandits: Theory and Application to Budgeted LLM Configuration Evaluation Advances in Neural Information Processing Systems 34 , pages =

Reference 100

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source=arxiv_source observed=2026-08-08T19:48:09.296553Z digest=sha256:1b994c8dff7e6f8b0353b4639c610fd46820cb09305e4a01cbde7591322b7788

Pith citing papers

No inbound Pith citation observations are available.