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Paper Citation Record · LEDGER

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

As of 12 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 2026-08-12T06:34:41.77262+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:e512aa93feec83905fb2abf926e75a1d9d6745b61d50c460f02134b463114dd5

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:c5ac1bc3dcad9e70df00f2552c03af84e7a377351f9c789012ce0b3a72567f4f

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=sha256:49a897c90d560c201c98a7c31e9f4446c04731222bf6f36a5387a67cb1ecf12b

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=sha256:267de7877b10b8d6ae80f869523e3258e54363584c2e7897b859546dce860479

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:bc2fc1fd859411d73b9dce13f94c064d1b3146e13d825ebf481d96916732b09b

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=sha256:91d2aa2ca68887b84681d9b79325ca5cd37d74db689106e113b434fc0383f9a6

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=sha256:1c7a9ba7aaa5d59e7f0b259fccae4e87a27c988d408fe1a27561d0ae3aab0523

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=sha256:9414324adf635ec7e38dc52b2de2a6861f547a72e8669ad80f493244a26b76f2

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=sha256:76518571af97cf11ee88db71fd5fad9a5a79e6ff3cf2db438a523d673afde184

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=sha256:93597b2da737ff635bbff7b72e9ffb30a25a997f5810bdc07dcabd8c9ee01865

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=sha256:66f6960b7c44bc277fe80baa8204792a7550c3b674037eb872309b1ad23f31fd

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:cee883e33cb3618c1c3963c809e03ab8da856693dd62ab0ebb8a663993339652

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:d648925550f89cc93e3cf46b5c06cc17ce381cc74c5080e69c95a2ce11ff1d78

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=sha256:3f3cf1ad3591face939b64755321f4773fbd38ad0ceb54438cf7ce41ea01daa1

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=sha256:9a426caa9c49a6664e14095456b2cb526a5d38c8f53d1a85ff3c682b7df16ca0

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=sha256:4ece177cd6be7625595ff1e64e20af4c315e728efdb9269f117e3c98642913b5

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=sha256:3c5015922a1b3941fe4cb3601fa38b0e148123752495208f16006a285e6606fc

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=sha256:2e7f98e5bb2bb070ef8b5efb3f50dbcd8ad5dee5ec223724e80212d34e33de85

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=sha256:8ba2b101fcc53d141868155d18be465cb5d24058e40769e75abec2d26315722e

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=sha256:28d3c1dccc5afe63f335eb4e6141027dac749a6291b2e6f28a94774088a9836d

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=sha256:67727cfa9a944c8398b324902f4420066786e073d9138cbdfad072e2e8828973

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=sha256:0d5e99158d0f23c1a4c2f6899226fc19a34eb7a3a36a1aa360907221b876a894

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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source=arxiv_source observed=2026-08-08T19:48:08.917793Z digest=sha256:c04b4b6cd2d8eb53602f0ba9a2db802eca7017d0e8942785947925e8531dbc6b

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=sha256:915de71c661750750c7ee0533417cddf9fcc9c6ebe90a371151cfe8e4e802183

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=sha256:53325acead0e3eed9ad5de1b8b4f6bb380365d203269d9ef824c35d77a959eae

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=sha256:09899a787e96bafa0dfdfe3ac161b820344deea559ef934b3aaf949f897496e5

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:bff2980fa5ee9030c8ac0a98c64eac62783b2412ce57ef2378b456a1cac92b3c

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

Reference 29

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source=arxiv_source observed=2026-08-08T19:48:08.942294Z digest=sha256:5cb9be62362ce4f62b3bd46cd45c8af1c2eaa18ba02db3d5e74307a4625f748c

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=sha256:4f0b5689a8e79e9a68dc1560206a79923d89ca7bd57ef046e168e3350e064a6b

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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source=arxiv_source observed=2026-08-08T19:48:08.952289Z digest=sha256:04b77031461efcd77cd8d6e275643af508e8a9bf4d38a05c6506de50a8026353

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:a1b7eeadddf95b923fd28d2a1c0f92a96796e3251e0af2390fd71c455ff034e3

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:e3f081a0a7082f3eea7b8d09e8555a486555448836c34d2d086ea3e30c232706

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:a3702bcd1c38785b75094ccaf9b50eee0b954aba7db4d7a8ef3ff54a7e1e6e85

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=sha256:70eb0dd3af097f3f5fca4ea2bcb0e15bbe2da95da6aefda73649cdf3d3a11466

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:c3439d1c02a2e2f5d7c435c1f36a2ca0dd8d400ff48ae85f0e1ab4d09fac82a7

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=sha256:088fed964525fe8d467c16e7da0ffe18b88e92d7b1ed4fefaab0ffcdc1897103

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:b591c53fd6bfd23e34a832dab84e000b459212569e7084d2574f2f7e667c1566

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:f1831ac23605712389c2027578f5dc7c7d7109b39e8d2490306a01d26fa83717

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:d703d0dec90fa7bcc101964f5256bdca125c6d1d7568b609379a17949e28c4e6

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:e7a76aa53a48c19ba55482f1d04b083331fa90e8964f90eac40cb20d574c1811

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=sha256:79f63ec218272a6e9c4873053b96b036d68f2dea30a9d2ea9879691ba43ece8b

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:f611e62e055e55923e6362ab5617b7f6f446aced434945ec1be6385b8b110723

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:b28c9c0831690737a2a0bdded2eb4cb6f69ae9b0e7915afcc2275166aaf31957

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=sha256:3f472d197cbb607ec20be908a3ddb79a96e386ca704ea71fb916113aa2459ab9

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=sha256:4e4ab09c8224b018b1f1b4a70797ca986fd696b5194c2f7ae33ba3b7e04c76bb

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=sha256:765a41a4937cced7c50eabf1fe29c68810442d7043315a2629ea3460984f985e

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=sha256:5ff50f6710bcdfc10ac641a9b37d9f09ba9ffc17091f87c1f4e8f54bebaae078

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=sha256:70d3381e58be2901fdb18eeccbb4c74d7a585763c920fe7049de05230c524c4b

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:a3887d17533533b1ec08a87d86cff72c725d9e045a6db17b4b9ab77ee7391801

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=sha256:2092a08ec9899d27e04eec016a96597a1a9faa772d1bc682072c40ca2c90f5d0

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=sha256:707186093c0f8e388c8cdf1a942a477e56b6e39813d6a66139b5a9cf0144d210

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=sha256:277c6d1668d59dd6eba51a4015758c97ffdf7efa9940dfe4efb76437e0b1aaba

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:a0cddc71f65b6fd59108128d3ea0e47da6ece5b68ffae4371f715b167ed157c6

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:fe9ea1a20263cedc4d945fac7616188846d3f639fbcfe929ec328e241f39e8f7

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=sha256:8ea4ea03b7ccd817746de61fa7228611b666a420f9ff813d25a0b649f1750c53

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=sha256:5f7a638f77256ec58f485e6c78855d0ec0d2435036a2b3acd45e590bb67655c8

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=sha256:94bc9c5c9a6da9546e7ad9f7bc13cb92e1c80a0635322f91224b30d6177e2e59

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=sha256:55313682deef90dbce9f7ba3da53c72d59242429033f3842bd5995f37ff1b4f9

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=sha256:9fa0dba7bb6f1de6235ccf2734e349f9504187f49fd15fb3f7f36d46b2801d8a

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=sha256:8a5db78737e31b88fdf1b90ff57b45196c47de405289fe71ea86b17088e27ac1

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=sha256:9407cbf57229da6378adb6e84eebcabdc36ca89183ab8998639a07ba7bdba0c3

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=sha256:0075b362e166d96048f1e549d878060685e6309a6219013e6d75383115d21ce9

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:d3aa2c5a04c0b20a28c6f3b91b33bddedd1848d848a7be5c1dfab59a94969b0b

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=sha256:991dfa1782d609d4fe232477112974b692518ccf30a86f218f692f74e06918ff

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=sha256:77bb7a254046896b97531cfd0aeed5d6f7259b38a620b0739b522c5e9851e46f

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:efe9b1310e60631a22361fe07f7bdd982c22aa1cfeb2fb1812e8a9a9c81a6c17

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=sha256:12cb4a9bdd433c5f34ba574f7aefdb3c5cdaf8f2906316ee364b82756534fc75

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=sha256:8c2f2ecb26448f8c632d06891734cf26e0a5808f6f93ae12db3ee628061670c5

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=sha256:2d88ec3bbe23e673abf73cd68d468ee6f465c176a7d1158f79e828ef14534a96

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=sha256:5443dbcdf7a8930d726fb6b1205774c4d41d7fb4314822b97f50059fee162bdd

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=sha256:53f1ba380c4020235ccf3fd374b022de1f00f8f6e2c975e3ad88e229008b4ca9

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:ba6c4ec175eebb054007d43214dba97b18b52fd6ce146e763f3fc1c8f4bf3aa1

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:fbd21b30d9ae5d43e484327bf03a6c65dbc56b269c69f4fc9a0276b5a9f59556

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=sha256:16b0069d644def8f238e0bed81001503dcdcb014177db8719d548979b2977d25

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=sha256:2bb4d3517ba46b10c8699c714fe57928294302ce4151489b8675c338b55ecc47

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=sha256:43853f68c969d28255288a05d75063500c3a1990711cbbeea33292b27d7bcc1d

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:eeb3630019238ce20fe8f3a744aabc5402efeea2868f5b26ab03b10620adcb51

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:aa67bb1b780db063c9f948083095f296269eaed52a2cbf6d899ff331b6f0e855

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=sha256:64462133fce748e55cb69b9f6e51837ee81ad648c9994489ddc1a7c91dd85049

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=sha256:78e1a121a13756f5494642eaf43877899a1335d66e3790afcafd867b8744ca69

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=sha256:6fea8285f8eb9836ea9e789a81e9d339fc5f2b14bf71dfabf15da8f846960173

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=sha256:64286c9200cb33879437d5aaf3456c4999bdffd91d6a54b4e5b91d68bb6945f9

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=sha256:8fa7e9328a36fa222a31e024e304a3ce1958709bef08112a1beab369830fc03c

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=sha256:9d5a34a3db86c6c9114dc0a01dc53cb9c103b456ffd66d7de6fc3a5564a5eaa6

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=sha256:6baddfb2735ce64eaffd181dc865dfc65719581f4500c3f5a43ba03884db3466

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:e804e15d40f69004d3655a2f3a403320fc9a0977c36e6618f2c18f1a079c8171

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:ab874b0b0042c4d683bbae99427a444dec5279fb81ff849bc81e0fa2b0b52061

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:b121e4f3491623b46a99f2333c61ce1325e4d58e3c2532266c6eaca53904b6a0

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:c43b055925ab7a4504035e8dc6b7383b7e4884d5198ea02684a3f36f0745213d

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=sha256:1c11928472e8e6b42e79d6b2f3e9185d5e4f4d7d94181aaa0b5939f479676440

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=sha256:5d780d642a9dba5178281f860baa2e90756245a89e3abfa7c56d98815d10ed00

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=sha256:489a1fce4783bc879c8b8ade33c14f8f7932c9a44e121947dd2026253062bf96

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:af9f15de63e694e7d7815003ac9d9ab7f64cc37d29bec585512ccea168b6d525

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=sha256:11c32bcf631eeeee971207a6aacbb3a7442ed55bd9c8c582150dc1b835bf5857

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:a2d26a262b97aea70f89abff686bb50171bd4f4f44e54c2dd16383fe0898fcac

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=sha256:708261ca90fb4fd55915f3fd93ab75d4dd44bd98f7b8f4946d8339d52a3412f4

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:d9b62a8d167406f079d55b763404c066114c60bd985f8c1fb2e4941e986d10b2

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=sha256:14a7a2dfa8b90bb592548323ae1fc27210c13af4e631fa78a32d2c77edc03ae9

Pith citing papers

No inbound Pith citation observations are available.