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Paper Citation Record · LEDGER

Offline Learning for Combinatorial Multi-armed Bandits

As of 10 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 3 inbound Pith citation observations for arXiv:2501.19300.

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

pith.paper-citation-record.v1
2501.19300 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:45:51.330020Z

measured 36 of 36 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:21:39.763211Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T13:01:03.227843Z

Reference resolution

33 of 33 outbound references displayed

  • verified exact0
  • verified fuzzy15
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation db8e2882-4d5e-4719-b39d-617a0ab8bac5 · outbound

This paper cites Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback.

Offline Learning for Combinatorial Multi-armed Bandits Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T20:45:51.240862Z digest=sha256:846c93fbc5880635c55f6bc32532f3e7eb2aa6b05b46d2bc794449ca972070f6

Observation 8c305033-b342-454c-bdb5-b6c45b5a5c44 · outbound

This paper cites org/CorpusID:260316010.

Offline Learning for Combinatorial Multi-armed Bandits org/CorpusID:260316010

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.245135Z digest=sha256:9a4f1d006fa1622240f107443d7279ed2f7a170372daea1c74a48d0d31f29a1a

Observation 7855778e-9c56-48fe-9df0-62f6d90cb6b0 · outbound

This paper cites Cost-Effective Online Multi-LLM Selection with Versatile Reward Models.

Offline Learning for Combinatorial Multi-armed Bandits Cost-Effective Online Multi-LLM Selection with Versatile Reward Models

Reference 10

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source=pdf_text observed=2026-08-09T20:45:51.260321Z digest=sha256:34d26bfb98241df490a81802c463199d7dbde7b8d7bf47db28ebf3a481d05451

Observation bbc163c9-358f-448a-b0be-ad6eb602ac49 · outbound

This paper cites org/CorpusID:235422620.

Offline Learning for Combinatorial Multi-armed Bandits org/CorpusID:235422620

Reference 12

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raw_fallback, observed 2026-08-09T20:45:51.567700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.266752Z digest=sha256:16667b69c3c3e60db348a593e48f4bd68bcc28f82ded140ecb1fe8a4568696aa

Observation 54697854-2ab7-445d-aded-fe9230791a52 · outbound

This paper cites Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor.

Offline Learning for Combinatorial Multi-armed Bandits Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Reference 14

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source=pdf_text observed=2026-08-09T20:45:51.272633Z digest=sha256:107570d4389b6d29ed9c71c6dbbe04be3a9d8b7ac01259984174222f0fd531b3

Observation 8af85bdc-b3b7-4c20-8188-b68f71918e83 · outbound

This paper cites org/CorpusID:28202810.

Offline Learning for Combinatorial Multi-armed Bandits org/CorpusID:28202810

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.275614Z digest=sha256:1ddd74e6c62afad69a1dc16ac91237d97395393dace8d3b1173cde630e0cde52

Observation 95527f5c-b25a-417f-bc83-1c8bf0faed81 · outbound

This paper cites org/CorpusID:211011033.

Offline Learning for Combinatorial Multi-armed Bandits org/CorpusID:211011033

Reference 18

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raw_fallback, observed 2026-08-09T20:45:51.541147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.284421Z digest=sha256:72863fac1608ef759cbcef8b3d933099705269148b92271e7291558a520f46b5

Observation 76af462e-7a05-49b3-8faf-063dfdb8550f · outbound

This paper cites Conservative Q-Learning for Offline Reinforcement Learning.

Offline Learning for Combinatorial Multi-armed Bandits Conservative Q-Learning for Offline Reinforcement Learning

Reference 19

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-09T20:45:51.287327Z digest=sha256:d2e3c924f44a4d9cc37957e1b5a9759116cc844497197ace82b6ddb41a6ac245

Observation 93148686-93fe-4156-b119-74e4ab0041cd · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Offline Learning for Combinatorial Multi-armed Bandits Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 20

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source=pdf_text observed=2026-08-09T20:45:51.290290Z digest=sha256:6f482cb151b135003de3a76c104c301cc85e0ccc132c3516284f7320b4e9ac26

Observation 9e3ea8a1-7526-4dba-bd8e-139450246a45 · outbound

This paper cites Combinatorial Logistic Bandits.

Offline Learning for Combinatorial Multi-armed Bandits Combinatorial Logistic Bandits

Reference 21

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source=pdf_text observed=2026-08-09T20:45:51.293340Z digest=sha256:d771c2973217d3b4b47dd531b99ed0789a16d76fa6e0d4bf3a43fbea80be4750

Observation 38fdfbfd-c5d2-4fed-873a-175b79d59611 · outbound

This paper cites org/CorpusID:208617840.

Offline Learning for Combinatorial Multi-armed Bandits org/CorpusID:208617840

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.296440Z digest=sha256:dfe2e62820ba7488b4bbcb2c6b6cfa2fbfe2e93e26e1ac6a6f2289c00feee378

Observation 6579d043-19b6-49cd-9ec0-21dd3b22a6c8 · outbound

This paper cites Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian.

Offline Learning for Combinatorial Multi-armed Bandits Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian

Reference 25

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source=pdf_text observed=2026-08-09T20:45:51.304986Z digest=sha256:22a55e5f95a7da101318599d5b268068fb41f657269390470e2345fc64403c6c

Observation 08f0f9f1-6674-45f7-809c-eb401a3af3e2 · outbound

This paper cites Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity.

Offline Learning for Combinatorial Multi-armed Bandits Pessimistic Q-Learning for Offline Reinforcement Learning: Towards Optimal Sample Complexity

Reference 27

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source=pdf_text observed=2026-08-09T20:45:51.310714Z digest=sha256:02984cd791c0d5249b8c7684de476097e2078bcd0ffaa8a45c28f9b88ddddb44

Observation be06bb87-33b5-4d46-add2-abc07efeb513 · outbound

This paper cites org/CorpusID:247159013.

Offline Learning for Combinatorial Multi-armed Bandits org/CorpusID:247159013

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.314366Z digest=sha256:c7327177654fb79f9bb1e98654fb540dc3c9b0d364c57e439408fcca4cb79b92

Observation 381b336d-2739-4898-a2c8-78d153bb1614 · outbound

This paper cites org/CorpusID:234826156.

Offline Learning for Combinatorial Multi-armed Bandits org/CorpusID:234826156

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.317544Z digest=sha256:ef271ebf8172c886f53cf3c86d9ebf82fbaa78e11f7c6bdfa3ee18d8c0353440

Observation 8d61b0e5-c68c-4f4c-839d-c83c32270c7e · outbound

This paper cites Combinatorial Bandits for Maximum Value Reward Function under Max Value-Index Feedback.

Offline Learning for Combinatorial Multi-armed Bandits Combinatorial Bandits for Maximum Value Reward Function under Max Value-Index Feedback

Reference 31

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local_arxiv, observed 2026-08-09T20:45:51.367607Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.323290Z digest=sha256:d11d1690347755da9e2e67fb51efc19c3b2608802f0d170539815718fd31ec4b

Observation b3948507-b6c0-493c-84d1-f140e1c85c37 · outbound

This paper cites Near-Optimal Offline Reinforcement Learning via Double Variance Reduction.

Offline Learning for Combinatorial Multi-armed Bandits Near-Optimal Offline Reinforcement Learning via Double Variance Reduction

Reference 32

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source=pdf_text observed=2026-08-09T20:45:51.326444Z digest=sha256:fe1096cbbbd8336634b957f818c3686d9f92183f666d1cd8b24fce9160d9562c

Observation 07807c96-acf2-4d08-a417-a12ef182ceb4 · outbound

This paper cites batch RL.

Offline Learning for Combinatorial Multi-armed Bandits batch RL

Reference 33

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raw_fallback, observed 2026-08-09T20:45:51.497389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.330020Z digest=sha256:81417d0d9f9fb37d78c907136c2b7d467ad2274698207a987c7f37534b84b4d1

Observation 344d2a49-3e32-46dc-9660-ddf9eb52c55a · outbound

This paper cites Chen, W., Wang, Y ., Yuan, Y ., and Wang, Q.

Offline Learning for Combinatorial Multi-armed Bandits Chen, W., Wang, Y ., Yuan, Y ., and Wang, Q

Reference 159

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.251749Z digest=sha256:3e6f65d6264b5d8ce346ad2d99c99923c4f4f6c5ae014ce02bded60a89a7d854

Observation f0d021d4-ce4c-4168-b817-aae430c59d10 · outbound

This paper cites Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization.

Offline Learning for Combinatorial Multi-armed Bandits Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization

Reference 1375

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source=pdf_text observed=2026-08-09T20:45:51.299080Z digest=sha256:6df08e2fce94901cdbf549c6c931f64fe82de2d6cd6bc7a4c4c32b536cf42273

Observation 81094f23-1291-4af3-b765-6014b6bf125e · outbound

This paper cites BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning.

Offline Learning for Combinatorial Multi-armed Bandits BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning

Reference 1716

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local_arxiv, observed 2026-08-09T20:45:51.473838Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.257220Z digest=sha256:635409460382f2a7e35914ad1eae6386e58a5a60974dfa9deb396237a6e0cc9c

Observation 3221d8a7-3f70-4945-8590-ff8aab70b250 · outbound

This paper cites Chen, W., Sun, X., Zhang, J., and Zhang, Z.

Offline Learning for Combinatorial Multi-armed Bandits Chen, W., Sun, X., Zhang, J., and Zhang, Z

Reference 1724

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raw_fallback, observed 2026-08-09T20:45:51.576296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.254515Z digest=sha256:1c0c53f4a8223cec49118bcb9baf90f9f8d2e0682f2cefb06c0f2f733ad1ba91

Observation b12ba690-c6da-4fe8-baba-40e184e47fbf · outbound

This paper cites org/CorpusID:5785954.

Offline Learning for Combinatorial Multi-armed Bandits org/CorpusID:5785954

Reference 2002

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.308050Z digest=sha256:a71f04c197e0cb90bbdd5efdbc0c34c4530dea7d28bbe7e39b0d105e8c3e9b8f

Observation b6597414-f24d-4d37-9692-0501639f9d68 · outbound

This paper cites Influence Maximization with Bandits.

Offline Learning for Combinatorial Multi-armed Bandits Influence Maximization with Bandits

Reference 2005

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source=pdf_text observed=2026-08-09T20:45:51.320267Z digest=sha256:e9970e8eb430e71ccda20b2946026440235c352a479a5714265dd38c750efb58

Observation 7cf04bf9-123b-47c6-8845-55e8bf2f7038 · outbound

This paper cites org/CorpusID:742580.

Offline Learning for Combinatorial Multi-armed Bandits org/CorpusID:742580

Reference 2015

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.234422Z digest=sha256:d8fbf2842e38cf10a7a02284b086d4e64c2946ede6e8dc787b511ef65b0d8c28

Observation f5c29039-d30e-42c7-8632-b2361c11eb78 · outbound

This paper cites Prompt Cache: Modular Attention Reuse for Low-Latency Inference.

Offline Learning for Combinatorial Multi-armed Bandits Prompt Cache: Modular Attention Reuse for Low-Latency Inference

Reference 2018

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source=pdf_text observed=2026-08-09T20:45:51.269548Z digest=sha256:5c342eb687d07f6ca75b0b9aa9ca4f1a92add56b2dd784d49dd8720a641fbf0e

Observation 426821e6-a2a3-4417-8b55-ab3aa0cc3396 · outbound

This paper cites Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning.

Offline Learning for Combinatorial Multi-armed Bandits Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning

Reference 2019

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source=pdf_text observed=2026-08-09T20:45:51.230499Z digest=sha256:010f392f106a7e40e9d2b532535bdc5062e2da2456aa5225cd72b0e87a4408e2

Observation d9085009-17ac-49fd-86da-a6e5a528f45b · outbound

This paper cites org/CorpusID:218595964.

Offline Learning for Combinatorial Multi-armed Bandits org/CorpusID:218595964

Reference 2020

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verified fuzzy
raw_fallback, observed 2026-08-09T20:45:51.549708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.281614Z digest=sha256:8415526c3dcbe4e9e628f4bff69bc0330987be665692569363eed1e8f30bafde

Observation 8b0f495f-916a-4b32-998d-8541f084a556 · outbound

This paper cites org/CorpusID:248498378.

Offline Learning for Combinatorial Multi-armed Bandits org/CorpusID:248498378

Reference 2021

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verified fuzzy
raw_fallback, observed 2026-08-09T20:45:51.593412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.248442Z digest=sha256:181b82ffe8ceadbf2f9400041f155ad4edab0fa9b673cf527b5d541165bb1f7f

Observation 7530a131-89a5-4de1-b794-08641b2ac8f1 · outbound

This paper cites Mobile Edge Intelligence for Large Language Models: A Contemporary Survey.

Offline Learning for Combinatorial Multi-armed Bandits Mobile Edge Intelligence for Large Language Models: A Contemporary Survey

Reference 2022

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source=pdf_text observed=2026-08-09T20:45:51.302066Z digest=sha256:60762a3b526549b8c147cfb56159551b7f0f77d62db3b0e020503f0a0fd35da3

Observation 1cf2222b-b99e-4bf3-aea8-01f2958ce89c · outbound

This paper cites org/CorpusID:265607979.

Offline Learning for Combinatorial Multi-armed Bandits org/CorpusID:265607979

Reference 2023

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verified fuzzy
raw_fallback, observed 2026-08-09T20:45:51.609509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T20:45:51.237555Z digest=sha256:e79f8c5aa2c180aa67e1695663f9ec0663a56f8cb6f7ca3d8ca0001bed2811a3

Observation 9a44dbf7-bfa7-473d-8879-edddb7f42f7b · outbound

This paper cites Federated Combinatorial Multi-Agent Multi-Armed Bandits.

Offline Learning for Combinatorial Multi-armed Bandits Federated Combinatorial Multi-Agent Multi-Armed Bandits

Reference 2024

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source=pdf_text observed=2026-08-09T20:45:51.263570Z digest=sha256:5d212179e0fd00c51ff144ad77bf4d10b58915fb91496bf4fcccd39c6cb7f8d2

Observation 84f67030-58b8-4fe6-92ad-096876af497c · outbound

This paper cites On Value Functions and the Agent-Environment Boundary.

Offline Learning for Combinatorial Multi-armed Bandits On Value Functions and the Agent-Environment Boundary

Reference 4039

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source=pdf_text observed=2026-08-09T20:45:51.278487Z digest=sha256:2aa14ad03935f580cec0fc485745695381615027df353b8e70ecd24a961cb54f

Pith citing papers

Observation f8ea145b-77bb-4e00-b5a3-9d4a7136a459 · inbound

A Unified Online-Offline Framework for Co-Branding Campaign Recommendations cites this paper.

A Unified Online-Offline Framework for Co-Branding Campaign Recommendations Offline Learning for Combinatorial Multi-armed Bandits

Reference 25

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no resolver link, observed 2026-08-07T13:21:39.763211Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:21:39.763211Z digest=sha256:e901770a761e1dfd27714c314d5f54aa1a448e6426bcdbd044b4b9d5ced0b3e3

Observation 10d820ea-91f9-4035-99eb-0e8e69edb66d · inbound

Best Arm Identification with Possibly Biased Offline Data cites this paper.

Best Arm Identification with Possibly Biased Offline Data Offline Learning for Combinatorial Multi-armed Bandits

Reference 2016

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:07:12.820368Z digest=sha256:58f138c56f2fd994b4a0075317504ddf53f93918d3542a1fd4fcaca15abc1bd6

Observation 48485c5d-b1a8-4be1-8234-88aa0f2e3e94 · inbound

Continuous Semantic Caching for Low-Cost LLM Serving cites this paper.

Continuous Semantic Caching for Low-Cost LLM Serving Offline Learning for Combinatorial Multi-armed Bandits

Reference 20

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verified exact
arxiv_id, observed 2026-05-11T13:01:03.233839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T02:32:28.923367Z digest=sha256:b405efef223c20c98e5b532d31ea3614434f7d1c8f4d7a1c2d4c3b98ce7a650f