Paper Citation Record · LEDGER

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management

As of 4 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2406.05358.

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

pith.paper-citation-record.v1
2406.05358 v3

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-24T00:35:41.483393Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T04:23:38.033851Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

verified exact4
verified fuzzy13
unresolved26
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 12c1b1ac-ddea-430c-a372-e15e3041560e · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.291332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 911acad8-fbb7-4191-82d3-87e278898f46 · outbound

This paper cites Balwally, G.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Balwally, G

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.298961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 744f24f0-0499-43ef-b3e7-92f4a97851b3 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.421934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e651b7d1-80fa-4729-980e-fa872aea7341 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.381795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5a5142a5-5051-427a-be0b-a14d24a592f4 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.435424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 561187d1-5bcf-403e-b974-2f8ffb8202ba · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.428523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 05942cf6-42f0-41fb-a36d-f617a73271a8 · outbound

This paper cites Dong, and Y.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Dong, and Y

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.373136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f25f101b-35c1-403d-a5bc-d64d0286148a · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.392121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 547f7bf1-2078-4fac-9cf4-9e664b93b925 · outbound

This paper cites Iyengar, R.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Iyengar, R

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.317013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8bfb8960-ba95-45dc-ab4b-d8fc80dba17c · outbound

This paper cites Topaloglu, et al.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Topaloglu, et al

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.425332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 86934709-fcec-40f4-af7a-7d5e3e1df442 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.418463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d3b7396b-60bf-4150-9e2d-b9fe6ffe1428 · outbound

This paper cites Reinforcement Learning for Jump-Diffusions, with Financial Applications.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Reinforcement Learning for Jump-Diffusions, with Financial Applications

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-24T00:35:55.789716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d7472ae3-6a2a-42bb-b48b-53f79eb087c7 · outbound

This paper cites Logarithmic regret bounds for continuous-time average-reward Markov decision processes.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Logarithmic regret bounds for continuous-time average-reward Markov decision processes

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-24T00:35:55.767241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f31c5e4a-6dec-4120-9882-830386633c37 · outbound

This paper cites Square-root regret bounds for continuous-time episodic Markov decision processes.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Square-root regret bounds for continuous-time episodic Markov decision processes

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-24T00:35:55.775103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 64caaf1b-6e55-4900-8a46-8d4d5c285103 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.395247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 09cd893d-456d-455e-9a4b-d112f615eee0 · outbound

This paper cites Hern \'a ndez-Lerma, X.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Hern \'a ndez-Lerma, X

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.338100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6a6d1618-43d1-4411-834f-82e33f1263ca · outbound

This paper cites Huang, and Y.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Huang, and Y

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.402828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fb1aa8f0-7928-4d84-a69f-4808e4b47957 · outbound

This paper cites Xu, and T.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Xu, and T

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.406674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fb1722f2-2793-4fb7-8ce2-10dfb56b0be6 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.409915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 983c5226-e085-46cb-938a-2ebcdbef423b · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.361330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation af6543f4-946f-4199-8b95-da03cebe88c6 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.398691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e76ea325-63a8-484a-9a1f-da29057b18a4 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.348696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 67caff39-eb46-4b5e-bd63-af2b58aba280 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Adam: A Method for Stochastic Optimization

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-24T00:35:55.781874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d20a9bcd-e563-48a1-973d-7e196a854270 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.378049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 24980786-46bc-4a0e-9902-4bb5e418ce7d · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.344661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 036decf9-5d43-4464-a9f6-76ca936e6bc0 · outbound

This paper cites Rusmevichientong, M.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Rusmevichientong, M

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.432304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6634607b-7993-4f44-be94-42860be73798 · outbound

This paper cites Nazari, L.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Nazari, L

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.295336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5a8d6d69-c9f8-4bce-b929-ad7686ce325b · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.385261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e6862ffc-59a0-4868-8807-d17c2485a7d3 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.341428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5807fed6-50f9-4a0b-b600-66c574b7d4d1 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.286815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 79c956a5-6614-4241-aa13-6251860b6c98 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.413674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9533ab71-8fea-46eb-a508-c511615a7cca · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.443790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 739512cb-15ee-4e1b-a2c9-748fe3441299 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.305475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 09660af2-b232-45d9-b1e2-d571ae097304 · outbound

This paper cites Blier, and Y.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Blier, and Y

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.439979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 110a388d-10bc-45c1-9cbc-0d9ea26b9f4b · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.352445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c82dfc27-9df7-4a14-b184-b8dff9967c34 · outbound

This paper cites Gao, and L.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Gao, and L

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.333717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5e4914f6-bde8-4544-bd9f-d542c44336de · outbound

This paper cites Zariphopoulou, and X.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Zariphopoulou, and X

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.388850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 812f8856-17fd-4099-9481-90ccd92f0906 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.355764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 080a0cce-2066-4627-9429-366a43e4da12 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.328076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e7ffe62a-2ccc-44a2-a77e-2cb9b200fe36 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.312981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2a5d9dba-4f66-4f7f-8e55-e72afb3a3512 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.320921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 71f71d8b-1f6c-4218-829a-2cfeb32ba775 · outbound

This paper cites an unresolved cited work.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Unresolved cited work

Reference 42

Resolution: unresolved; raw_fallback, observed 2026-05-24T00:35:56.324294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4e17d63e-db6a-4146-af47-cb9b4a3224af · outbound

This paper cites Tang, and D.

Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management Tang, and D

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T00:35:56.309583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Pith citing papers

Observation d236428f-cfe0-44a9-b0a2-40acbdaa2310 · inbound

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning cites this paper.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-12T04:23:38.033851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.