{"as_of":"2026-08-09T20:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a8d418ad0d4d40ededaaea86a4cea97aab2e028c81a70ed0a7b7aa7591eb7986","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T19:16:00.551909Z","state":"measured"},{"denominator":33,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":33,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.17031/citation-record","integrity":"/paper/2607.17031/integrity","json":"/paper/2607.17031/citation-record.json","paper":"/paper/2607.17031"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:57.422248Z","title":"Security-constrained unit commitment for electricity market: Modeling, solution methods, and future challenges,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:57.422248Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:490fab56ab978f1744be62a983f123fc59eec2f5a6883663e511d25f88f8e770","observation_id":"7f8f128b-6a77-458c-aaa8-4cca51530e13","resolution":{"observed_at":"2026-08-01T19:15:57.422248Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:57.526794Z","title":"Machine learning approaches to the unit commitment problem: Current trends, emerging challenges, and new strategies,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:57.526794Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:17d55cc33de42269bfbb03f7a7e713bd1f2035cc94e6475e812e4ed1c0ac9638","observation_id":"12ba4ce5-770c-4755-b130-11046c03f9d5","resolution":{"observed_at":"2026-08-01T19:15:57.526794Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:57.613808Z","title":"Learning to solve large-scale security-constrained unit commitment problems,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:57.613808Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:77a4d9521a78a7a357f6f64701a2d48304ff5ae532cd9e6dab04640ee5717ee9","observation_id":"2bf6b95b-3de2-4769-9442-cd9bd69fa818","resolution":{"observed_at":"2026-08-01T19:15:57.613808Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:57.696588Z","title":"Is learning for the unit commitment problem a low-hanging fruit?","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:57.696588Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:a742aca3c6ec1f93834e003543a5cf8bb894e6cd336e32d5e6a59e65ae8199a3","observation_id":"bf6607dd-3e8f-4996-8bbe-02d08ebe3ec9","resolution":{"observed_at":"2026-08-01T19:15:57.696588Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:57.786552Z","title":"Deep reinforcement learning explanation-assisted integer variable reduction method for security-constrained unit commitment,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:57.786552Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:792f90459fdecd4337720826ea87d9dede099a529c048c6d869a0aa9908d9b2f","observation_id":"f65f5bb1-28d8-4d6e-a146-bae368d07547","resolution":{"observed_at":"2026-08-01T19:15:57.786552Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:57.932327Z","title":"Feasibility-guaranteed machine learning unit commitment: Fuzzy optimization approaches,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:57.932327Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:4be868fa90290858e3793ac3ab0d302dbfe00769ac9f867a9dab3b9ef26f8b33","observation_id":"0549d6ec-703d-4732-9ab8-2e1139ebfd22","resolution":{"observed_at":"2026-08-01T19:15:57.932327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.02788","last_updated":"2026-04-03T06:55:32Z","snapshot_observed_at":"2026-07-06T22:52:06.460027Z","submitted_at":"2026-04-03T06:55:32Z","title":"Structure-Aware Commitment Reduction for Network-Constrained Unit Commitment with Solver-Preserving Guarantees","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.02788","snapshot_observed_at":"2026-08-01T19:15:58.035154Z","title":"Structure-aware commitment reduction for network- constrained unit commitment with solver-preserving guarantees,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:58.035154Z"},"links":{"cited_paper":"/paper/2604.02788","citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:b8f35451523defc477e8d52ad71234a851d9789a5c520aa51ac3d9305c0fcddf","observation_id":"6349f19b-6f92-433a-a364-c50dc51d7f9a","resolution":{"observed_at":"2026-08-01T19:15:58.035154Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:58.141339Z","title":"Successive fixing for large-scale security-constrained unit commitment using first-order methods,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:58.141339Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:10c44f7b8d7cf702a3fd8191f9dd6e26ded6b0ba10f2e60a66cb78c8f5dd1805","observation_id":"07810a11-af97-434b-af27-a544bec149df","resolution":{"observed_at":"2026-08-01T19:15:58.141339Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:58.211836Z","title":"Applying reinforcement learning and tree search to the unit commitment problem,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:58.211836Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:c3ae41a1abcd536e850f998cfed616f1b4a97b1f6834cc69ed6501b97c02696b","observation_id":"f75d4674-0d23-461a-ad86-687da4751e14","resolution":{"observed_at":"2026-08-01T19:15:58.211836Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:58.279360Z","title":"Reinforcement learning and A* search for the unit commitment problem,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:58.279360Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:c987317649d75840694745458272f74ed726a823eb767c179d78adda7a1b4293","observation_id":"eeff24ed-5221-4b07-ac53-96ecb1a82ef4","resolution":{"observed_at":"2026-08-01T19:15:58.279360Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:58.363787Z","title":"An optimization method-assisted ensemble deep reinforce- ment learning algorithm to solve unit commitment problems,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:58.363787Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:9a2973ff6489f81b709103f57a9536f72afe953c4d9a7e0cf37bd0c4e1443644","observation_id":"c6d98115-febc-4260-a6e3-ab2a4b39dcad","resolution":{"observed_at":"2026-08-01T19:15:58.363787Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:58.552681Z","title":"Deep reinforcement learning-assisted convex programming for AC unit commitment and its variants,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:58.552681Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:be82e32ec5a8b22c280304acd3d49fe472e4b516d5b87ce872dc174b98a76554","observation_id":"02a5d51d-c179-4f01-bba3-8464fdb0532c","resolution":{"observed_at":"2026-08-01T19:15:58.552681Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:58.628838Z","title":"Deep reinforcement learning based model-free optimization for unit commitment against wind power uncertainty,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:58.628838Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:2a645949e4648476a18121c0adeba649009c7edd65f467b5409046b88ac19561","observation_id":"0c32908b-ee39-43a6-aee9-4874f7701d16","resolution":{"observed_at":"2026-08-01T19:15:58.628838Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:58.706358Z","title":"Look-ahead unit commitment with adaptive horizon based on deep reinforcement learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:58.706358Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:4635408a9d54911fe3c540cc3ae8bbb5d7a137b7928a961e92f02661e6052275","observation_id":"4d1c6d06-7a69-4951-b166-c919e073be08","resolution":{"observed_at":"2026-08-01T19:15:58.706358Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:58.782720Z","title":"Expert knowledge data-driven based actor-critic reinforcement learning framework to solve computationally expensive unit commitment problems with uncertain wind energy,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:58.782720Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:03e6894870cb58ab6159fae81ca9041ff87030135efeec2d40a2fd570a336d81","observation_id":"395b4551-f4ce-4177-b3a3-ca4881b16284","resolution":{"observed_at":"2026-08-01T19:15:58.782720Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:58.918661Z","title":"Graph reinforcement learning with auxiliary temporal- graph convolutional neural network for unit commitment,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:58.918661Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:81eb3399c101b04304e63cf76f3bf455430a419c41c463664425e2da0ebbe0f6","observation_id":"16085065-ed52-487b-a9b7-9bd389ae2199","resolution":{"observed_at":"2026-08-01T19:15:58.918661Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:59.042734Z","title":"Adapting quantum approximation optimization algorithm (QAOA) for unit commitment,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:59.042734Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:56053f3896d3b0d26f28f709dde92387187c931a6b9d97daabe8c7d17daff27c","observation_id":"77f75384-197a-4c6d-b3ac-93d57983afbd","resolution":{"observed_at":"2026-08-01T19:15:59.042734Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.15917","last_updated":"2026-06-06T22:54:38Z","snapshot_observed_at":"2026-08-07T17:57:33.775945Z","submitted_at":"2025-02-21T20:15:40Z","title":"Qubit-Efficient Quantum Annealing for Stochastic Unit Commitment","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.15917","snapshot_observed_at":"2026-08-01T19:15:59.113685Z","title":"Qubit-efficient quantum annealing for stochastic unit commitment,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:59.113685Z"},"links":{"cited_paper":"/paper/2502.15917","citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:faaae57f69e121128c41b81d33138492c94db4ea833968fb0c2f8ce5c646c387","observation_id":"6ddbf048-d6d7-41b2-9c4a-4feca28a33a5","resolution":{"observed_at":"2026-08-01T19:15:59.113685Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:59.189594Z","title":"Novel resolution of unit commitment problems through quantum surrogate Lagrangian relaxation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:59.189594Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:47059fcfdc35e5dfa94e945e1b9a4d8475278fc41e4fe193ecc7d29ebf099a7b","observation_id":"2799a045-407c-4ba0-b247-851a24291799","resolution":{"observed_at":"2026-08-01T19:15:59.189594Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:59.262412Z","title":"A fast quantum algorithm for searching the quasi-optimal solutions of unit commitment,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:59.262412Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:c3785d81845c157dd4928b85b6cfadea82af183a5375b87555e82ea6da8d4769","observation_id":"6aee5eac-93d1-47a2-b2e4-bf64c90cc405","resolution":{"observed_at":"2026-08-01T19:15:59.262412Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:59.337251Z","title":"Exact quantum algorithm for unit commitment optimization based on partially connected quantum neural networks,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:59.337251Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:220d66b211422f0acc8a4674b6eaec8bf140af0e6469e31e8c3927ae6be61318","observation_id":"05edf046-dd93-49bb-9493-6cb271b4a3f1","resolution":{"observed_at":"2026-08-01T19:15:59.337251Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:59.428327Z","title":"Quantum reinforcement learning based two-stage unit commitment with integration of virtual power plants and renewable energy,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:59.428327Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:22bff3804367c3d3b10f6ecdd86d45dcda562566e597531197e67f2c2b19a667","observation_id":"4c1d98cb-b05b-49d1-90b7-410e6754b727","resolution":{"observed_at":"2026-08-01T19:15:59.428327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:59.494622Z","title":"A new hybrid quantum-classical algorithm for solving the unit commitment problem,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:59.494622Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:fb708ab34499d0336a082dd48da07de1400f8f1539eeb04ee22a19fd5e162c70","observation_id":"e34e3adb-eb5c-4839-aac7-e07c463d2662","resolution":{"observed_at":"2026-08-01T19:15:59.494622Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:59.583647Z","title":"D 2-UC: A distributed-distributed quantum-classical framework for unit commitment,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:59.583647Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:db0be4dda1fb9e1d8cf108c2c02f816c9cb438fa628bdd354302d6059ce73f2a","observation_id":"bd29a708-e9e5-4730-8cb0-f153c7f71329","resolution":{"observed_at":"2026-08-01T19:15:59.583647Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:59.730479Z","title":"Leveraging quantum comput- ing for accelerated classical algorithms in power systems optimization,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:59.730479Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:804e2d28e04fe96a9c345599e2325c44a5773d915212f4ef2f8e38d22a96a522","observation_id":"8a9cdd01-d9d5-44fe-a19e-022f48b6042f","resolution":{"observed_at":"2026-08-01T19:15:59.730479Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:59.806469Z","title":"A survey on applications of quantum computing for unit commitment,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:59.806469Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:951cda69db85197498dc11e2d9b0bbd827e1df92ccd32f5366227d4990820e13","observation_id":"a3949b78-0313-4bb7-9fa5-e9dd3510d4b2","resolution":{"observed_at":"2026-08-01T19:15:59.806469Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:59.889264Z","title":"QHSAC-Unit- Commitment,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:59.889264Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:41b6e053c6d0b8a01a9a15a95fd2a83f2f62840be2ba2232ca2c16c551e4af2c","observation_id":"0a7cbb0f-fffe-4080-be34-af68f80caf94","resolution":{"observed_at":"2026-08-01T19:15:59.889264Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:15:59.965438Z","title":"UnitCommitment.jl: A Julia/JuMP optimization package for security-constrained unit commitment,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T19:15:59.965438Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:19f3a744020438b5bb01255648b923ad8c8956859fafcd85974cb7617712cf73","observation_id":"9029c5de-b3fd-4321-a755-e3fa7984a2fe","resolution":{"observed_at":"2026-08-01T19:15:59.965438Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:16:00.111976Z","title":"Attention is all you need,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T19:16:00.111976Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:0a69e22d2834c899f3f09a21fadf703cd0c470cc0d28cb84f0e1bce3df3ba9a2","observation_id":"18f7280c-8378-44c3-837f-d83dd921d356","resolution":{"observed_at":"2026-08-01T19:16:00.111976Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:16:00.204453Z","title":"Supervised learning with quantum-enhanced feature spaces,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T19:16:00.204453Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:64ddafe79c5646a526dc777dbcbe5753f9c97830345f333f7fadf0f075f0c4b0","observation_id":"7bc55d2d-93d1-41ce-bc48-b9ee9b19a50f","resolution":{"observed_at":"2026-08-01T19:16:00.204453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:16:00.289789Z","title":"Random features for large-scale kernel machines,","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-01T19:16:00.289789Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:a11f2f21149aa341e0443e2a6e26d63f53dddacca121a4c59e8ec15fca062da0","observation_id":"1cd402c2-e401-4ebe-8468-36e2ebb78139","resolution":{"observed_at":"2026-08-01T19:16:00.289789Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:16:00.428221Z","title":"Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-01T19:16:00.428221Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:9e53c31df882e50d7a405e3b588983eec6ed8c8b6cee84fa37a17e15d1e41eec","observation_id":"ca261006-50ad-437b-9ab7-2bee45124ba8","resolution":{"observed_at":"2026-08-01T19:16:00.428221Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T19:16:00.551909Z","title":"JuMP 1.0: Recent improvements to a modeling language for mathematical optimization,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-01T19:16:00.551909Z"},"links":{"citing_paper":"/paper/2607.17031"},"observation_digest":"sha256:8b9cd451dc9440929d2d968e7a96bd5df550154be1871db01b281c1dfebe93a2","observation_id":"262f526a-77c0-4a99-a229-29904078633b","resolution":{"observed_at":"2026-08-01T19:16:00.551909Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.17031","last_updated":"2026-07-19T02:28:51Z","latest_version":1,"primary_category":"eess.SY","snapshot_observed_at":"2026-08-08T17:20:26.482342Z","submitted_at":"2026-07-19T02:28:51Z","title":"Feasibility-Aware Security-Constrained Unit Commitment via Hybrid Soft Actor-Critic with Quantum-Sampled Features"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":33,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":33},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.17031."}