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Paper Citation Record · LEDGER

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification

As of 11 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2607.22644.

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

pith.paper-citation-record.v1
2607.22644 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T10:13:34.225362Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

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  • verified fuzzy0
  • unresolved28
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 908d6c08-f856-45d2-8941-58d5376725e7 · outbound

This paper cites 2015 13th international conference on document analysis and recognition (ICDAR) , pages=.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification 2015 13th international conference on document analysis and recognition (ICDAR) , pages=

Reference 1

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source=arxiv_source observed=2026-08-02T10:13:30.531190Z digest=sha256:fd510d8459bb89c864a290127a269e5e96d5817178fb8b048a7eaa1e67cab08b

Observation a4e48e41-6b67-4219-8c84-1fa085dde518 · outbound

This paper cites 2015 13th international conference on document analysis and recognition (ICDAR) , pages=.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification 2015 13th international conference on document analysis and recognition (ICDAR) , pages=

Reference 2

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source=arxiv_source observed=2026-08-02T10:13:30.686043Z digest=sha256:9d6e53ad8f4a82843a458e1c4f2ca584bcfe185977c417f24df4a203ce9aa33a

Observation 1d9dd619-ff31-41df-87f5-41c7b7939b65 · outbound

This paper cites 2017 14th IAPR international conference on document analysis and recognition (ICDAR) , volume=.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification 2017 14th IAPR international conference on document analysis and recognition (ICDAR) , volume=

Reference 3

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source=arxiv_source observed=2026-08-02T10:13:30.855053Z digest=sha256:f3dc102ae785a766474b56fc77dac53cec9718204b8e93a8ed6a941fdfbcbec8

Observation bce3eb2a-6975-408f-8c52-a00cb3965e8d · outbound

This paper cites Joint European conference on machine learning and knowledge discovery in databases , pages=.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Joint European conference on machine learning and knowledge discovery in databases , pages=

Reference 4

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source=arxiv_source observed=2026-08-02T10:13:31.036038Z digest=sha256:ba5e067089d268828a3b39dcba85553f92c58bb31451487c7ac8adc977d20eb0

Observation 2375950f-5215-43d5-a145-f361b7064b65 · outbound

This paper cites Ninth international conference on document analysis and recognition (ICDAR 2007) , volume=.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Ninth international conference on document analysis and recognition (ICDAR 2007) , volume=

Reference 5

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source=arxiv_source observed=2026-08-02T10:13:31.210345Z digest=sha256:862908e8c4ae95ed7bd75738b5fc33f35397fc7b842e318b93f064e440b1f4b7

Observation 428e5325-68bb-43f7-a5d3-de637f755e0a · outbound

This paper cites ACM Computing Surveys (CSUR) , volume=.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification ACM Computing Surveys (CSUR) , volume=

Reference 6

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source=arxiv_source observed=2026-08-02T10:13:31.384074Z digest=sha256:b4c2cdd8ca6e1130d43f891158eba6ac9f94f598b34088a6377dd74e4b378a46

Observation b3f9c484-11bf-4bf6-b90e-6c6232a47d72 · outbound

This paper cites DocBERT: BERT for Document Classification.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification DocBERT: BERT for Document Classification

Reference 7

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source=arxiv_source observed=2026-08-02T10:13:31.544769Z digest=sha256:f2943f42d51108fca7d54cb679f94a80b80e1a95e14a143fb7f5bb29a401b5a6

Observation 8ab05c78-f2c9-4253-999a-ef042fcb66bb · outbound

This paper cites International conference on machine learning , pages=.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification International conference on machine learning , pages=

Reference 8

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source=arxiv_source observed=2026-08-02T10:13:31.676756Z digest=sha256:c9a493e0d4aecb490f081d58929137646d2590bf11c6677f53448aae52a0d524

Observation 435b216e-b74e-4a0e-8463-5650fbc5c7cc · outbound

This paper cites Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=

Reference 9

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source=arxiv_source observed=2026-08-02T10:13:31.808569Z digest=sha256:3df7a7db50446d73292c62b827a2ff4eb98224f447975c912b78354db4546593

Observation b9b65cb5-f1c9-44e1-9636-4d1f523d0919 · outbound

This paper cites International Conference on Computational Science , pages=.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification International Conference on Computational Science , pages=

Reference 10

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source=arxiv_source observed=2026-08-02T10:13:31.981989Z digest=sha256:626dcf02d14ef9f471a4c02de3a0c73f1c0c25bf063b9204404c0b6e49891186

Observation e77359bd-324d-478b-8c50-164c646487be · outbound

This paper cites an unresolved cited work.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Unresolved cited work

Reference 11

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source=arxiv_source observed=2026-08-02T10:13:32.099739Z digest=sha256:f2c9c80087a613adc2b8015f078f194bafcb58221c165813b1caa2f0fb17c8dd

Observation 8fc1589e-74a3-46e1-a928-3dbc6d660c35 · outbound

This paper cites 2022 26th International Conference on Pattern Recognition (ICPR) , pages=.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification 2022 26th International Conference on Pattern Recognition (ICPR) , pages=

Reference 12

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source=arxiv_source observed=2026-08-02T10:13:32.204451Z digest=sha256:eab3400d5967e76d0ebf546510547f7305f5d8256ac14fff12ebb9c365e04ba7

Observation cd1c42e6-944d-404b-98e9-d377bed3095c · outbound

This paper cites Proceedings of the European Conference on Computer Vision (ECCV) , year =.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Proceedings of the European Conference on Computer Vision (ECCV) , year =

Reference 13

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source=arxiv_source observed=2026-08-02T10:13:32.314023Z digest=sha256:68fc231b9f57f76c058bd27ad700c6ffdf412b94d90723bc231ce73c6f68f042

Observation 9b4a8039-0f48-4a6c-a49a-0a4d2e4abd39 · outbound

This paper cites Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) , year =.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) , year =

Reference 14

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source=arxiv_source observed=2026-08-02T10:13:32.421252Z digest=sha256:39e79f96d1f5cc9d21e37518982d00b8684ee45745dbec7b6e17c5ef7016ca56

Observation 95ed4ab2-0185-499d-a759-7f8b53379d98 · outbound

This paper cites Barto and Sridhar Mahadevan , title =.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Barto and Sridhar Mahadevan , title =

Reference 15

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source=arxiv_source observed=2026-08-02T10:13:32.523690Z digest=sha256:81e82a1ef2ce25c4c841e0219fb74c06acc225f1394f6c123ed51032b9f1a6cc

Observation e2ca5850-4066-4443-92f3-4169d1b8883b · outbound

This paper cites Sutton and Doina Precup and Satinder Singh , title =.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Sutton and Doina Precup and Satinder Singh , title =

Reference 16

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source=arxiv_source observed=2026-08-02T10:13:32.599235Z digest=sha256:098c142b745f9b4bc6e9c990efe1bd7908948506fcb343a2c526e2e1227a73fd

Observation acf40c96-889d-4365-81e3-158a6ae80825 · outbound

This paper cites an unresolved cited work.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Unresolved cited work

Reference 17

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no resolver link, observed 2026-08-02T10:13:32.675476Z

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source=arxiv_source observed=2026-08-02T10:13:32.675476Z digest=sha256:392a67d28c6b61a087f85fba21f49e714dcb2e53e2a29be9cbfdf256b5a93428

Observation d0f1b11b-8172-4c74-97c3-2d554a5e2516 · outbound

This paper cites CVPR , year =.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification CVPR , year =

Reference 18

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source=arxiv_source observed=2026-08-02T10:13:32.764482Z digest=sha256:780f1f0106ce003cf8639de826850fcbd97f1d692b37f61c9c57f066894c4778

Observation 5cdafc33-0e87-4711-94f9-a79748d52a51 · outbound

This paper cites Le , title =.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Le , title =

Reference 19

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source=arxiv_source observed=2026-08-02T10:13:32.868704Z digest=sha256:98dd0af1bf777e3d34761f161dd97d7a3dd1d2d3180ea0b5cf77309599105f00

Observation f318f4d5-db27-4a24-9275-49e9ecf1a462 · outbound

This paper cites ICCV , year =.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification ICCV , year =

Reference 20

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source=arxiv_source observed=2026-08-02T10:13:32.940787Z digest=sha256:2bd1de8b5ccef066f5af2edd46f724a2d4a88926aa295eaf2f7aee967b8cd499

Observation 87eee5b6-4517-4638-829b-d400317b6eec · outbound

This paper cites Proximal Policy Optimization Algorithms.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Proximal Policy Optimization Algorithms

Reference 21

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source=arxiv_source observed=2026-08-02T10:13:33.051354Z digest=sha256:15470a02c0e3681565f54527f3fbb585bb85f984b5b3a04a2d9841496dfde412

Observation 97465d93-9372-4786-beee-ffbf12478477 · outbound

This paper cites Proximal Policy Optimization Smoothed Algorithm , journal =.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Proximal Policy Optimization Smoothed Algorithm , journal =

Reference 22

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source=arxiv_source observed=2026-08-02T10:13:33.225349Z digest=sha256:090acf73df8f542484fb081632038003c82432db7999084be63808a92b3da0c8

Observation 735d4061-f10c-4437-8256-e32f7d14ac6f · outbound

This paper cites Neural Processing Letters , volume =.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Neural Processing Letters , volume =

Reference 23

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source=arxiv_source observed=2026-08-02T10:13:33.430438Z digest=sha256:c8bf50c6ed3e8c70feb46154972de0001acaa7ffda26c2a0304a44ba8aa397b5

Observation 9d9ddae1-52aa-47a8-a302-d593a7d88e87 · outbound

This paper cites Soft Adaptive Policy Optimization.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Soft Adaptive Policy Optimization

Reference 24

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source=arxiv_source observed=2026-08-02T10:13:33.588899Z digest=sha256:642c46c0b704edc306cf083d58368d63f95af1a9bd546bc869de4d902ab9a8f6

Observation c2ef33be-0b3f-46c7-8cee-78ffd127024f · outbound

This paper cites arXiv preprint arXiv:2509.21282 , year =.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification arXiv preprint arXiv:2509.21282 , year =

Reference 25

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source=arxiv_source observed=2026-08-02T10:13:33.716383Z digest=sha256:da03c5e5a8411177431ba080c34c6b94cd385393f05f73709baad1a08d3cc57d

Observation 3151ae6e-7660-4183-8154-ff1c2474c2b4 · outbound

This paper cites Advances in Neural Information Processing Systems (NeurIPS) , year =.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Advances in Neural Information Processing Systems (NeurIPS) , year =

Reference 26

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source=arxiv_source observed=2026-08-02T10:13:33.889687Z digest=sha256:16c47d549e9d53e7137c2ca78a9f5994b9b56badaf9dd7b99d4d2cae0276a623

Observation 31bd682f-f001-46af-9bbc-98d836ae54ba · outbound

This paper cites Mastering Diverse Domains through World Models.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification Mastering Diverse Domains through World Models

Reference 27

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source=arxiv_source observed=2026-08-02T10:13:34.030240Z digest=sha256:3fa440ab1d00094c5124d58436c14a97dbe129a1909c22e7b294d9cadeaeeb36

Observation e5e5ee07-57a8-490e-a65d-05d3cca576b4 · outbound

This paper cites OpenReview , year =.

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification OpenReview , year =

Reference 28

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source=arxiv_source observed=2026-08-02T10:13:34.225362Z digest=sha256:1487451471b0976ffe284f1fe1d74076c14a959daf0ed9c711f29b95d64da179

Pith citing papers

No inbound Pith citation observations are available.