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Paper Citation Record · LEDGER

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning

As of 11 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 1 inbound Pith citation observation for arXiv:2502.05537.

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

pith.paper-citation-record.v1
2502.05537 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:03:05.612017Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T04:53:10.425398Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T04:55:54.390079Z

Reference resolution

58 of 58 outbound references displayed

  • verified exact1
  • verified fuzzy44
  • unresolved12
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c6c77021-e3ee-4112-b584-715da3499ddf · outbound

This paper cites Hindsight experience replay.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Hindsight experience replay

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.542013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 80bc2e2b-6d14-497d-bdfc-a089e43c1f27 · outbound

This paper cites Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set

Reference 2

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Source-reported events for the cited work

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Observation a3983750-a7ef-4efb-baee-21a3f9c5dd32 · outbound

This paper cites The option-critic architecture.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning The option-critic architecture

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 1a98aa2a-c9a5-4ac4-81ab-4cc5cad97071 · outbound

This paper cites Neural Combinatorial Optimization with Reinforcement Learning.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Neural Combinatorial Optimization with Reinforcement Learning

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 346bc664-227d-4ce3-a8de-a8a07546b3b2 · outbound

This paper cites Machine learning for combinatorial optimization: A methodological tour d’horizon.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Machine learning for combinatorial optimization: A methodological tour d’horizon

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.499738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation fc86a519-a3bf-44ae-8b0b-2c73b28e54d1 · outbound

This paper cites RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation fb027c3d-feae-4b3b-9fa6-fc9845017877 · outbound

This paper cites Models and algorithms for combinatorial optimization problems arising in railway applications.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Models and algorithms for combinatorial optimization problems arising in railway applications

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.483727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.356856Z digest=sha256:9eba6b392e2dd899d5ea9bcbd045893efb084e3f6a8692a84fd4a69e23e4094e

Observation ee40282e-4239-4fe5-9e56-a68597b703dc · outbound

This paper cites Applying gis and combinatorial optimization to fiber deployment plans.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Applying gis and combinatorial optimization to fiber deployment plans

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.468790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 521f4a51-8597-44ec-81a6-908180e21947 · outbound

This paper cites Improving optimization bounds using machine learning: Decision diagrams meet deep reinforcement learning.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Improving optimization bounds using machine learning: Decision diagrams meet deep reinforcement learning

Reference 9

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raw_fallback, observed 2026-08-08T19:03:06.454089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.366486Z digest=sha256:edad636893cc04cab91e3416bf23480f095a9fa83f79abfecba0c5edae8ea7ac

Observation 3954d364-95aa-4a94-964d-af507c0c7b21 · outbound

This paper cites Contingency-aware influence maximization: A reinforcement learning approach.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Contingency-aware influence maximization: A reinforcement learning approach

Reference 10

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raw_fallback, observed 2026-08-08T19:03:06.439691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 6be00938-74af-433d-9b9f-c98995bc0d09 · outbound

This paper cites Learning to perform local rewriting for combinatorial optimization.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Learning to perform local rewriting for combinatorial optimization

Reference 11

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raw_fallback, observed 2026-08-08T19:03:06.424938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.376450Z digest=sha256:aa12f338da619dcaed7d6f0f1c26b6a260391bffc35643dd2afe2eef0751e2c8

Observation 405cfe16-e1c0-4ae7-a095-5ad040e51962 · outbound

This paper cites Discriminative embeddings of latent variable models for structured data.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Discriminative embeddings of latent variable models for structured data

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.409130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 41e48dd5-391d-42c7-af87-dc38750570eb · outbound

This paper cites Feudal reinforcement learning.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Feudal reinforcement learning

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.394011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.385410Z digest=sha256:ce4719f2d5635bffa74394270d374c5fef06231b0476cf302ee27157175bee66

Observation 44c5ad8f-c132-4ef7-a2f7-b547bc87892f · outbound

This paper cites Learning heuristics for the tsp by policy gradient.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Learning heuristics for the tsp by policy gradient

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.377570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.389827Z digest=sha256:8da1b8bb33c681d6f64e589892ce7bad920e52a1f40ff3eb1a1cdb2257464d1e

Observation 6fe79b74-02fa-480e-89a8-c4f60958210f · outbound

This paper cites Learning Permutations with Sinkhorn Policy Gradient.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Learning Permutations with Sinkhorn Policy Gradient

Reference 15

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 74691e8f-3ad9-44be-a04c-ad897a778d18 · outbound

This paper cites Generalize a small pre-trained model to arbitrarily large tsp instances.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Generalize a small pre-trained model to arbitrarily large tsp instances

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.361992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.399133Z digest=sha256:52a65089d110a54d107135254c34032dd355f9c159cfc19bb1efd4916c4547d6

Observation aa9ad8b4-5f2d-45dc-88e7-2bfdba7dc047 · outbound

This paper cites Deep Sensitivity Analysis for Objective-Oriented Combinatorial Optimization.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Deep Sensitivity Analysis for Objective-Oriented Combinatorial Optimization

Reference 17

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local_arxiv, observed 2026-08-08T19:03:05.709732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation bbf9f8ec-f50d-4c7f-94d2-e164ca2ec384 · outbound

This paper cites node2vec: Scalable feature learning for networks.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning node2vec: Scalable feature learning for networks

Reference 18

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raw_fallback, observed 2026-08-08T19:03:06.346542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.407984Z digest=sha256:cfe446e9da91d344de6015e6a4589cc8be41e079a10ecf64d06ba7203513c779

Observation 92a868bb-bc63-406c-80e1-5ec618317c80 · outbound

This paper cites Double q-learning.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Double q-learning

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.412203Z digest=sha256:eaa2d845c67dcee9493a62d4644c1e69996dbc4cf74c96289563287a7b1d361a

Observation e64f3668-ab28-4724-a84d-f348a2ae5b93 · outbound

This paper cites Efficient active search for combinatorial optimization problems.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Efficient active search for combinatorial optimization problems

Reference 20

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raw_fallback, observed 2026-08-08T19:03:06.317716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 40361bc2-72a8-449d-8805-1839b7c52e35 · outbound

This paper cites Convergence of stochastic iterative dynamic programming algorithms.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Convergence of stochastic iterative dynamic programming algorithms

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.422052Z digest=sha256:cbe4ef64b24c9ec9403b3dcf6845901b124c7908d56d9ce922350b5a1e64082a

Observation 0a24db4d-80a0-4aab-965b-bac1f1209523 · outbound

This paper cites Deep reinforcement learning approach to solve dynamic vehi- cle routing problem with stochastic customers.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Deep reinforcement learning approach to solve dynamic vehi- cle routing problem with stochastic customers

Reference 22

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raw_fallback, observed 2026-08-08T19:03:06.285983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 9a21f23e-ea64-4fd5-b9ad-2ed62956359d · outbound

This paper cites Maximizing the spread of influence through a social network.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Maximizing the spread of influence through a social network

Reference 23

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raw_fallback, observed 2026-08-08T19:03:06.268148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 2785ac3a-62da-4da8-b57b-e8fa6f42d1f1 · outbound

This paper cites Learning combinatorial optimization algorithms over graphs.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Learning combinatorial optimization algorithms over graphs

Reference 24

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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 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.436959Z digest=sha256:633ab30abe29937304e00ea354fdfbfdf20b598860b907182c76fece1a5e0a74

Observation a2bb0535-2d7a-4016-9f72-c87ce1aecf1d · outbound

This paper cites Semi-supervised classification with graph convolutional networks.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Semi-supervised classification with graph convolutional networks

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.235822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 1b5389a6-f425-482d-9f06-05742a76a4ca · outbound

This paper cites Attention, learn to solve routing problems! In International Conference on Learning Representations, 2018.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Attention, learn to solve routing problems! In International Conference on Learning Representations, 2018

Reference 26

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raw_fallback, observed 2026-08-08T19:03:06.219988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.447001Z digest=sha256:77d1634dc1430b07f8725dde6c4a79b01d0a108b005d8f8118377d36ba9fbe07

Observation 4d7c55bb-7df6-4aab-82dc-e25f51a54107 · outbound

This paper cites Hierarchical deep reinforcement learning: Integrating temporal abstraction and intrinsic motivation.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Hierarchical deep reinforcement learning: Integrating temporal abstraction and intrinsic motivation

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.203778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.451936Z digest=sha256:1e7ab5583c3c8b3b8b0f234de1f0ec2c237156530d7f96155b654d3d4c951655

Observation 2cef4d40-8a12-49c3-9d15-bc00610ca9e1 · outbound

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

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Pomo: Policy optimization with multiple optima for reinforcement learning

Reference 28

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no resolver link, observed 2026-08-08T19:03:05.457088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:03:05.457088Z digest=sha256:8960fd19c777c33fca3733f421a6bf020154a8094149602893f0bf378456f0c5

Observation 80205747-990b-40b6-84b7-8ba9815b5e4e · outbound

This paper cites Mind dataset for diet planning and dietary healthcare with machine learning: dataset creation using combinatorial optimization and controllable generation with domain experts.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Mind dataset for diet planning and dietary healthcare with machine learning: dataset creation using combinatorial optimization and controllable generation with domain experts

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.176470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.461851Z digest=sha256:f4d867c9d4a89ff1d934d754a09ee80e2982066c24ebaafbb06ec932bc9806a8

Observation a2ac4060-43e0-48b6-8bd0-2fb646b53ad6 · outbound

This paper cites Learning multi-level hierar- chies with hindsight.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Learning multi-level hierar- chies with hindsight

Reference 30

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no resolver link, observed 2026-08-08T19:03:05.466597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:03:05.466597Z digest=sha256:29002d2e394bd865a3a7edc743d71a016b337e315c2929d5d8d7e6b71d0266c7

Observation eec2e7cf-b65b-412b-a3d1-67f2ee418624 · outbound

This paper cites Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.149253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.471258Z digest=sha256:a5a538de37934c453b7277f56d088077b42755528185eddbb665c379029cb1e0

Observation 53b0f20a-d133-472e-95af-d7c7763a832c · outbound

This paper cites Deep-learning-based wireless resource allocation with application to vehicular networks.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Deep-learning-based wireless resource allocation with application to vehicular networks

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.134149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.475492Z digest=sha256:99a484baa4ccd2a43693ee78bf6b2a6e21b1e79041797270f0837c248fa539f4

Observation bb161e73-031d-4ca3-97ce-e66c00828c30 · outbound

This paper cites Graph Foundation Models: Concepts, Opportunities and Challenges.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Graph Foundation Models: Concepts, Opportunities and Challenges

Reference 33

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no resolver link, observed 2026-08-08T19:03:05.479770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:03:05.479770Z digest=sha256:b8e9294196eeddbb8ad379b0e109a5b11e96d2ce76d117ad12bd48bba2ae34d0

Observation 30db095e-8246-41c7-bd14-7d30d5f6072c · outbound

This paper cites A learning-based iterative method for solving vehicle routing problems.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning A learning-based iterative method for solving vehicle routing problems

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.119961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.484808Z digest=sha256:f1a3fb9762d4789efbee90cad64e2a4e664a4513941a787e8b50b304b3f00fe1

Observation 9a4472fc-995c-4090-96df-e06f811c33ba · outbound

This paper cites Reinforcement learning for combinatorial optimization: A survey.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Reinforcement learning for combinatorial optimization: A survey

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.105831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.488997Z digest=sha256:9388baf2666cc7dde0a595a14842f02d91431565750f9be4d09470ccabed7a27

Observation 967d589c-0932-4ad7-811d-7b08b4d7210d · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Playing Atari with Deep Reinforcement Learning

Reference 36

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no resolver link, observed 2026-08-08T19:03:05.494362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:03:05.494362Z digest=sha256:85c676248e486574f55d2153fe1d2d53c8bf54a1744d516a9beb00c552ee0447

Observation 207edfba-cd35-45a7-9863-a94c18bb49a8 · outbound

This paper cites Human-level control through deep reinforcement learning.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Human-level control through deep reinforcement learning

Reference 37

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no resolver link, observed 2026-08-08T19:03:05.499797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:03:05.499797Z digest=sha256:690ebf29e9ef472bbadd55c00401b148836d7ffb8cfe3e263c48ab3e51a71999

Observation cf0b18ab-bd0d-429a-9660-4e91e7b6b0d7 · outbound

This paper cites Data-efficient hierarchical reinforcement learning.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Data-efficient hierarchical reinforcement learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.081050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.504359Z digest=sha256:0a957f54447316424ec07536df7977f11c2825c7be54ebf0ded2ee06e3924fdd

Observation 2ff9a79b-80bf-4460-8447-9033028d33bb · outbound

This paper cites Reinforcement learning for solving the vehicle routing problem.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Reinforcement learning for solving the vehicle routing problem

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.065490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.509865Z digest=sha256:78f61710ecb2f4478eab5741a68cdc4fb2cfa2020ff99c463fc3e6a66f59351d

Observation 246a2440-7e7b-43bc-af6b-ae762afb04a0 · outbound

This paper cites Solo: search online, learn offline for combinatorial optimization problems.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Solo: search online, learn offline for combinatorial optimization problems

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.048989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.514510Z digest=sha256:d4e29e345b59b9b32895c91ee9f278f5a6500b66c053e8689d5734c0e9ac4194

Observation 83b47402-5b46-4d48-ad9d-f6127206dc96 · outbound

This paper cites Active screening for recurrent diseases: A reinforcement learning approach.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Active screening for recurrent diseases: A reinforcement learning approach

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.033330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.526265Z digest=sha256:70eb045bf680127d499e68f2a9823e2537fa207def35e2ad9786b24cd98a1002

Observation 8b6c6c81-7f71-49d5-af77-7c80f94e8b0f · outbound

This paper cites Adaptive influence maximization with myopic feedback.Advances in Neural Information Processing Systems, 32, 2019.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Adaptive influence maximization with myopic feedback.Advances in Neural Information Processing Systems, 32, 2019

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.017390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.531358Z digest=sha256:b16a48f3232b6f8a5acbf9196d90f809a62507fd5f35ab7c071956e13d9ed479

Observation 828aafdf-ef8f-4fef-89bf-07e24994a913 · outbound

This paper cites Deepwalk: Online learning of social repre- sentations.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Deepwalk: Online learning of social repre- sentations

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:06.002672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.536450Z digest=sha256:7ca81c43eaf5578ff5349411d3b300892d6f988124652ae5e956ad06e3399695

Observation 9a8c371d-4573-41fe-abc6-965b6d67feb0 · outbound

This paper cites Scarselli, M.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Scarselli, M

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:05.986934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.542776Z digest=sha256:a5481fafff51ec47344dd01d8e01ffcb7fd23a92a590ddfe7c2e139e5d98631b

Observation 3b84c475-f100-4b82-aca3-724f22386111 · outbound

This paper cites Combinatorial optimization with physics-inspired graph neural networks.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Combinatorial optimization with physics-inspired graph neural networks

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-08T19:03:05.548651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:03:05.548651Z digest=sha256:3312877800c8c21e3f523b9286866c1b5e7aa3f3de01d8c5ae7b24ddf0b2def4

Observation d58d75d6-008c-4983-9f35-cf0c142f8d09 · outbound

This paper cites Learning to predict by the methods of temporal differences.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Learning to predict by the methods of temporal differences

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:05.958959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.553555Z digest=sha256:3070a8477ad747ec21f099324cd7e6aacc12dc7341a2dbc2afd3459d29d8960e

Observation 87d164f2-5c43-4c6c-854f-37a091e712aa · outbound

This paper cites Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Between mdps and semi-mdps: A framework for temporal abstraction in reinforcement learning

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:05.943619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.558800Z digest=sha256:7691c89edae8a6912803fb38d77f8b0a87f9866cf641d32aefd139ab3ca6fcf5

Observation f83cec7f-51d8-46ce-bb53-7d15a57cd815 · outbound

This paper cites Time-constrained adaptive influence maximization.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Time-constrained adaptive influence maximization

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:05.926788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.562939Z digest=sha256:a76aa5f9bd1d5161946ee7e419ba57c14653c33423aef9f5e32ef6691ea318d1

Observation 279574b4-c7a4-4f92-85b6-13b4b0a75da0 · outbound

This paper cites Graph attention networks.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Graph attention networks

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:05.908402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.567015Z digest=sha256:1b6148167c6453e38178122b4241cca51702d74e59e35f7db922e73171a39b2f

Observation d64edccd-f62f-4dcc-be02-b3ef8e8cd0e6 · outbound

This paper cites Feudal networks for hierarchical reinforcement learning.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Feudal networks for hierarchical reinforcement learning

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:05.890658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.571246Z digest=sha256:de39b33fb9f4206cd36f812922e8a2de9be58d7c2407141648380c0711d48f18

Observation 761b4a4b-41cc-4472-836b-2eae7c724760 · outbound

This paper cites Q-learning.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Q-learning

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:05.873513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.576211Z digest=sha256:bce8768bdf3c10e693187d4e423d79e5c5a1da051008b8fa28ac430ff720e804

Observation 94f9e66f-b35b-41b9-8587-bfd7d718a5b7 · outbound

This paper cites On efficiency in hierarchical reinforcement learning.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning On efficiency in hierarchical reinforcement learning

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:05.857250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.581755Z digest=sha256:bfde5aa5b7c6bb08f6e920e2b197255728ebc8f15f0e0475d2327121335b6dff

Observation dcb0eca0-bb02-48f1-8da4-797527bdb221 · outbound

This paper cites an unresolved cited work.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-08T19:03:05.838649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.587774Z digest=sha256:d10a49334866f66c76aed5f583ff0fa1fde694c9f892721688367d59009368e2

Observation 49ba5402-4cf3-4dd3-8839-9d705c867b04 · outbound

This paper cites How Powerful are Graph Neural Networks?.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning How Powerful are Graph Neural Networks?

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-08T19:03:05.592590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:03:05.592590Z digest=sha256:67a89e86378b0641d6f61be9503e058db276be03bcce306ddbf365532ae7f326

Observation 23ad6750-cbdc-4758-b9ac-cac85fe42033 · outbound

This paper cites Accelerating Exact Combinatorial Optimization via RL-based Ini- tialization - A Case Study in Scheduling.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Accelerating Exact Combinatorial Optimization via RL-based Ini- tialization - A Case Study in Scheduling

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:05.821556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.597802Z digest=sha256:6e863dbdd9d1970464f94228e01c5b697fcc3dbb9eff251b796aa63c3f7f9863

Observation e364317d-dd16-435b-b6a0-fb87109b78ec · outbound

This paper cites Gnnexplainer: Generating explanations for graph neural networks.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Gnnexplainer: Generating explanations for graph neural networks

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:05.805142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.602875Z digest=sha256:d1d56c2c37873b18831ddb237aaeed98b8e4335e20a6fbfa8de3adc4e7e3057a

Observation d38485cb-03f0-466e-b2e2-d4abaa383722 · outbound

This paper cites Graph transformer networks.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Graph transformer networks

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T19:03:05.788657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.607378Z digest=sha256:200ba458cf4678a7ba7d1d5539c23bb528e0e9772a4fa9cfd71653bc20be3a03

Observation b8b130ab-4d76-4cf8-bdee-1637f0c75ed7 · outbound

This paper cites Graph neural networks: A review of methods and applications.

Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning Graph neural networks: A review of methods and applications

Reference 58

Resolution
malformed identifier
raw_fallback, observed 2026-08-08T19:03:05.773978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-08T19:03:05.612017Z digest=sha256:912ded29835b15d7ccc07dd472ae40c940ec43588431f6ad55f9941a0b269c44

Pith citing papers

Observation 2a5b9ce3-0b75-478c-b9e1-ec527baf48a4 · inbound

Demonstrating Real Advantage of Machine-Learning-Enhanced Monte Carlo for Combinatorial Optimization cites this paper.

Demonstrating Real Advantage of Machine-Learning-Enhanced Monte Carlo for Combinatorial Optimization Sequential Stochastic Combinatorial Optimization Using Hierarchal Reinforcement Learning

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-18T04:55:54.392627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-18T04:53:10.425398Z digest=sha256:6521fe6d71dfb33e9da83424f8a10b5984288ec50139a526935b313df6dacff2