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Paper Citation Record · LEDGER

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling

As of 9 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2605.23957.

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

pith.paper-citation-record.v1
2605.23957 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T22:17:02.000552Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

20 of 20 outbound references displayed

  • verified exact1
  • verified fuzzy17
  • unresolved2
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4c7fde88-cdb3-40ee-a0d8-2dd56837c030 · outbound

This paper cites Bertsekas.Dynamic Program- ming and Optimal Control, Vol.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Bertsekas.Dynamic Program- ming and Optimal Control, Vol

Reference 1

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 6e65a6e0-a5b4-4918-bd5a-8558fbb22096 · outbound

This paper cites Pickardt, and Mengjie Zhang.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Pickardt, and Mengjie Zhang

Reference 2

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verified fuzzy
raw_fallback, observed 2026-07-07T14:23:52.291406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 718b3a96-12c5-4794-8c95-a32eb62bb452 · outbound

This paper cites Burke, Michel Gendreau, Matthew Hyde, Graham Kendall, Gabriela Ochoa, Ender ¨Ozcan, and Rong Qu.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Burke, Michel Gendreau, Matthew Hyde, Graham Kendall, Gabriela Ochoa, Ender ¨Ozcan, and Rong Qu

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 20993e33-0ccd-46f7-b932-fff97390cd15 · outbound

This paper cites Analyzing bandit-based adaptive operator selection mechanisms.Annals of Math- ematics and Artificial Intelligence, 60(1–2):25–64,.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Analyzing bandit-based adaptive operator selection mechanisms.Annals of Math- ematics and Artificial Intelligence, 60(1–2):25–64,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-07-07T14:23:52.312052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation e6e77293-5ab1-46e0-81df-fb18991ce2c2 · outbound

This paper cites Thompson.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Thompson

Reference 5

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verified fuzzy
raw_fallback, observed 2026-07-07T14:23:52.306542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation ad7e7d15-4abd-4673-8b30-853637f2be4f · outbound

This paper cites Efficient dispatching rules for scheduling in a job shop.International Journal of Pro- duction Economics, 48(1):87–105,.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Efficient dispatching rules for scheduling in a job shop.International Journal of Pro- duction Economics, 48(1):87–105,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T22:17:02.000552Z digest=sha256:f9c6bf7175991fcb5595ed1cf5b45fb257517f11815c47ffaf7aa57aca8e225c

Observation d742d117-f083-43b5-8229-4c580770c017 · outbound

This paper cites Multi-objective parameter configuration of machine learn- ing algorithms using model-based optimization.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Multi-objective parameter configuration of machine learn- ing algorithms using model-based optimization

Reference 7

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verified fuzzy
raw_fallback, observed 2026-07-07T14:23:52.303147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T22:17:02.000552Z digest=sha256:7e6ef87b140689ea44cbb101416198122211f8e9fcd5a5f8ce605e8f8890fc2a

Observation 929bede3-e817-4c2f-91d2-90b3baa67d15 · outbound

This paper cites Discovering dis- patching rules from data using imitation learning: A case study for the job-shop problem.Journal of Scheduling, 21(4):413–428,.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Discovering dis- patching rules from data using imitation learning: A case study for the job-shop problem.Journal of Scheduling, 21(4):413–428,

Reference 8

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verified fuzzy
raw_fallback, observed 2026-07-07T14:23:52.304968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T22:17:02.000552Z digest=sha256:f214f289f0747807102f352ee6e095cc267053e06b9adbc14f8026f3e7a404ad

Observation 726795cc-fc72-4a6c-b4ff-6a4da8a9cf1c · outbound

This paper cites Learning dispatching rules using random for- est in flexible job shop scheduling problems.International Journal of Production Research, 57(10):3290–3310,.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Learning dispatching rules using random for- est in flexible job shop scheduling problems.International Journal of Production Research, 57(10):3290–3310,

Reference 9

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verified fuzzy
raw_fallback, observed 2026-07-07T14:23:52.308463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T22:17:02.000552Z digest=sha256:cbd2f5fccc8e27bce656576adff12a11aa382f047a0cc1e1829145703f1d8c56

Observation 3392c878-6979-40a6-a7ee-05edb632497f · outbound

This paper cites POMO: Policy optimization with multiple optima for reinforcement learning.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling POMO: Policy optimization with multiple optima for reinforcement learning

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T22:17:02.000552Z digest=sha256:c00ed3b6b7bd81259a8536abc43afe24cd452afc635b2211c2bc29cefd005d7d

Observation 8c37f3eb-1d7b-428b-b664-736ddac205a6 · outbound

This paper cites ASKSSA-CNN-BiLSTM: A novel time se- ries forecasting model for stock price prediction based on an enhanced sparrow search algorithm.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling ASKSSA-CNN-BiLSTM: A novel time se- ries forecasting model for stock price prediction based on an enhanced sparrow search algorithm

Reference 11

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation f491dbc1-5733-44ee-861e-a36393d28ab7 · outbound

This paper cites Evolution of heuristics: Towards efficient auto- matic algorithm design using large language model.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Evolution of heuristics: Towards efficient auto- matic algorithm design using large language model

Reference 12

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verified fuzzy
raw_fallback, observed 2026-07-07T14:23:52.319858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation bce947d9-2214-4f59-9b59-3ae34a69b4d5 · outbound

This paper cites MRBMO: An enhanced red-billed blue magpie optimization algorithm for solving numerical optimization challenges.Symmetry, 17(8):1295,.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling MRBMO: An enhanced red-billed blue magpie optimization algorithm for solving numerical optimization challenges.Symmetry, 17(8):1295,

Reference 13

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verified fuzzy
raw_fallback, observed 2026-07-07T14:23:52.317761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 6d68a7d9-5cfa-4dcf-a2c2-93e54182aad4 · outbound

This paper cites an unresolved cited work.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Unresolved cited work

Reference 14

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raw_fallback, observed 2026-07-07T14:23:52.294507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation ce7da306-7581-4157-be70-6a8300823551 · outbound

This paper cites an unresolved cited work.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Unresolved cited work

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 0efc52f5-c0bb-440b-b37e-2521a14670e1 · outbound

This paper cites ScheduleNet: Learn to solve multi-agent scheduling problems with reinforcement learning.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling ScheduleNet: Learn to solve multi-agent scheduling problems with reinforcement learning

Reference 16

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arxiv_id, observed 2026-07-01T14:05:46.966504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation ed5786b4-182a-4b95-8970-f785f9ed9544 · outbound

This paper cites Pawan Kumar, Emilien Dupont, Francisco J.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Pawan Kumar, Emilien Dupont, Francisco J

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 960e7820-f3ce-43fd-ab38-edd59e77e9b5 · outbound

This paper cites TSWOA: An enhanced WOA with triangular walk and spiral flight for engineering design optimization.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling TSWOA: An enhanced WOA with triangular walk and spiral flight for engineering design optimization

Reference 18

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verified fuzzy
raw_fallback, observed 2026-07-07T14:23:52.296257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 092ce64d-aa20-4dd9-a769-f71589856e70 · outbound

This paper cites ReEvo: Large language models as hyper-heuristics with reflective evolution.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling ReEvo: Large language models as hyper-heuristics with reflective evolution

Reference 19

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verified fuzzy
raw_fallback, observed 2026-07-07T14:23:52.297968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a14b4fe4-d162-4442-90f8-9514785b00f0 · outbound

This paper cites Learning to dispatch for job shop scheduling via deep reinforcement learning.

Low-Cost Labels, Reliable Choices: Rollout-Calibrated Hyper-Heuristics for Job Shop Scheduling Learning to dispatch for job shop scheduling via deep reinforcement learning

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-07-07T14:23:52.301404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Pith citing papers

No inbound Pith citation observations are available.