{"as_of":"2026-07-23T08:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:18998d0e444d30c9b72e429aca96dbf6292a46923123e5111513b50dc25a7b2d","coverage":[{"denominator":23,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-28T18:01:11.592565Z","state":"measured"},{"denominator":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-07-23T06:31:01.910684+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/2606.00883/citation-record","integrity":"/paper/2606.00883/integrity","json":"/paper/2606.00883/citation-record.json","paper":"/paper/2606.00883"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T18:01:11.592565Z","title":"Impedance circuit model of grid-forming inverter: Visualizing control algorithms as circuit elements,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:19807f88fa16a6c0ba636b0ced9d1153541944d4174a8ce7ef234c426bfdb30f","observation_id":"8fd24942-069f-4818-934f-6d415f4a24dc","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Unified impedance model of grid-connected voltage-source converters,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:4b5b5e3a12be37d46c2b515cf806c6a62dbae6d2b0e3b11070bc30ceea644122","observation_id":"43bdb85f-fb77-4bad-8135-1f575349f565","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Power system stability with a high penetration of inverter-based resources,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:9920bfa227ffe82c88407ade41505a0e576c0eb388a0310b1b89f61704f52c87","observation_id":"516ceb56-d775-4122-92c3-2933b327e730","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Large-signal stability of grid-forming and grid-following controls in voltage source converter: A comparative study,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:7bd41edb75298befa7621ed64c3550ecf1f95f2c12980e69118b538bfeba2805","observation_id":"8bd41649-c8f2-491e-897d-4ad5144bfa94","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":null,"venue":null,"work_id":null,"year":1992},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:ec26adb404ae7af8858483048927e38a410336a0a72b9b46a84a3197880f19a6","observation_id":"e28989a8-1411-45f4-a4d9-8bec14f64581","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Comparison and selection of grid- tied inverter models for accurate and efficient emt simulations,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:fc3d5d9bba6235bf81807998e20cdebb83592b30b3639afb5a24f9c023a4607c","observation_id":"8588e420-031f-490d-badb-f661b79a9063","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"LaSalle and S","venue":null,"work_id":null,"year":1961},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:2c9e55b5ffc460a46003ab0ba9377b42537855139cb014c7b5341d0508d16dc0","observation_id":"f8a3f5a9-5438-4a7b-a5e2-ca90c0e59dbf","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Complete large- signal stability analysis of dc distribution network via brayton-moser’s mixed potential theory,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:ed82fa6add250878a2ff481ea6c7e095ffe69975ea3c511a7dbaadee6ab99829","observation_id":"793ff95b-77d4-4b9c-ade3-5985ecf1f1ba","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Pll synchronization transient stability analysis of a weak-grid connected vsc during asymmetric faults,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:f253aab5e6b02d4a0dbb025c1d9b76eef25bb68dedccded67406c7ccf8c44fcd","observation_id":"13fb4848-18c4-40c3-b070-bf6887dbd0f8","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Large-signal stability analysis of two-stage cascaded dc/dc converter systems using sum-of-squares programming,","venue":null,"work_id":null,"year":2076},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:c0a8e8f1e163fca28ce95f95e84e5898916bf9f8021cfc90524934226dc4daa5","observation_id":"bcaf6537-68a1-4834-8e22-d7d3fc5e84a4","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"pii/0893608","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T11:29:50.205278Z","title":"Approximation capabilities of multi- layer feedforward networks","venue":null,"work_id":"7366e5ed-58b5-48e3-9599-08679e8cc95f","year":1989},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:0c5a41357d39d6291844ba559c84a099c71335e28b8423a7be5c2c6a309e2e65","observation_id":"0aaf319a-e181-4598-ab2d-d698a2959675","resolution":{"observed_at":"2026-06-28T18:02:26.857229Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-23T06:31:01.910684+00:00","source":"crossref"},{"observed_at":"2026-07-23T06:30:56.940895+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T18:01:11.592565Z","title":"Computing lyapunov functions using deep neural networks,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:573c634813a6ddbb0663ebdaed2dad7218a408c501617438c6ae63515826eb1d","observation_id":"570d1536-dd7e-4380-9f93-3638d368edcf","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"The lyapunov neural network: Adaptive stability certification for safe learning of dynamic systems,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:94fee757fc710bfe15adc70b8cd8ffa975eb29f63818994ed670cf197e523a98","observation_id":"f5e00277-11d1-44a9-afb2-cb38768d52f0","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Neural lyapunov redesign,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:dbf7ce791009ff95b9dd3d7113cf33fb6adfee7070ca618b8be897bff2d80660","observation_id":"eef33a7f-0ad7-4a08-a153-b214d5551ea9","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Neural lyapunov control,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:8500df6ebcc9aff7b51bab901e4fd719c5935048786c3b7182cda76aeb1c1662","observation_id":"788d1049-5569-4a88-bee6-2d3c5d05681f","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"A neural lyapunov approach to transient stability assessment of power electronics-interfaced networked micro- grids,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:462cf956a01d96cf80fefad28501f97691384a59ae68a7fb6b51b29533d0877e","observation_id":"7edb81b7-56e0-474d-bf5e-abb62207e9bd","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Neural lyapunov based transient stability analysis of networked grid-forming inverters with unknown internal dynamics,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:d246957e8f8e8dc48c7cd47c13aa062babc83db1967ea3cc405cb3cfc07ce324","observation_id":"521a6da8-8f20-465d-8907-2d9eef3e6ea2","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"An improved neural lyapunov method for transient stability assessment of networked microgrids,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:8a9708712801a4faace30eb66405efa5206c33890583c44f9d42e3e7fba8c3bc","observation_id":"542eb3bc-d244-4652-ae71-1ed52fa838b1","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Dissipation-based dynamics-aware learning scheme for transient stability analysis of networked black-box grid- forming inverters,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:82f3955123093dfb8c5043993f388534964befd2b5a6411a9c095488acf375ee","observation_id":"78d36bf9-20ef-48d8-88d4-948b648d39b5","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"δ-complete decision procedures for satisfiability over the reals,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:dd4c0de15d312cf5af8bc5462ecc8abec40758f8e4cf8c1fd65aeadca4e48c04","observation_id":"d6a5ed38-3bcf-40c0-923e-32cee37ca4aa","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Learning to stabilize high-dimensional unknown systems using Lyapunov-guided exploration,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:9ed002bbaa196a3ac88e3db5df59663c85c9e145dfbe257fda8f4059a1c496af","observation_id":"701604e4-6ae3-4777-bac6-ea4fb9f81244","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":"Interactive control of coupled micro- grids for guaranteed system-wide small signal stability,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:44fdd601379dccd976e7b19df7e921c66b156e0763a81ce657b714580c49891e","observation_id":"2a9af670-e02d-4293-8224-6c1bb6077f34","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","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":"2026-06-28T18:01:11.592565Z","title":null,"venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-28T18:01:11.592565Z"},"links":{"citing_paper":"/paper/2606.00883"},"observation_digest":"sha256:b4b729785848c3667b07f344ab6bf303807c607a00b9ea68618e00f6b6d8182f","observation_id":"27b4a76c-4356-4828-bd94-c415e421c6be","resolution":{"observed_at":"2026-06-28T18:01:11.592565Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.00883","last_updated":"2026-05-30T20:35:54Z","latest_version":1,"primary_category":"eess.SY","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-30T20:35:54Z","title":"Lipschitz-Enforced Machine Learning Framework for Accelerating Transient Stability Analysis of Networked Grid-Interactive Inverters"},"reference_resolution":{"displayed":23,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":22,"verified_exact":1,"verified_fuzzy":0},"total_outbound_references":23},"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":"2026-07-23T06:31:01.910684+00:00","source":"crossref"},{"observed_at":"2026-07-23T06:30:56.940895+00:00","source":"retraction_watch"}],"thesis":"As of 23 July 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2606.00883."}