{"as_of":"2026-08-21T16:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:62e593e8372e65e48bc3fba6190d2961cfdc1e2cace967539164dcad21d2f07e","coverage":[{"denominator":17,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-25T06:49:16.926107Z","state":"measured"},{"denominator":20,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":20,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T02:49:23.888427Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-09T22:46:35.974297Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2603.24489","snapshot_observed_at":"2026-07-11T22:22:42.030937Z","title":"Model predictive path integral control as preconditioned gradient descent,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.04006","last_updated":"2026-07-04T20:02:17Z","snapshot_observed_at":"2026-08-16T17:56:54.400393Z","submitted_at":"2026-07-04T20:02:17Z","title":"Finite-Sample Closed-Loop Stability of Model Predictive Path Integral Control for Linear Time-Invariant Systems","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-11T22:22:42.030937Z"},"links":{"cited_paper":"/paper/2603.24489","citing_paper":"/paper/2607.04006"},"observation_digest":"sha256:6e64b1c8f98052b8b3e97bf0e1164f0fe53e772c8445d8b6fc92a5e394b460cf","observation_id":"4d11b687-ec5f-4596-a8e6-30190708c9c5","resolution":{"observed_at":"2026-07-11T22:22:42.030937Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"cited_work":{"arxiv_id":"2603.24489","doi":null,"metadata_source":"pith","pith_arxiv_id":"2603.24489","snapshot_observed_at":"2026-07-09T22:46:35.974297Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","venue":"math.OC","work_id":"152cfda8-4c72-47b8-8b68-04217348b4e0","year":2026},"citing_paper":{"arxiv_id":"2607.06945","last_updated":"2026-07-08T03:14:19Z","snapshot_observed_at":"2026-08-21T06:23:28.059055Z","submitted_at":"2026-07-08T03:14:19Z","title":"Stochastic Stability of Nonlinear MPPI via Contraction Theory and Control Lyapunov Functions","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-09T22:38:13.447241Z"},"links":{"cited_paper":"/paper/2603.24489","citing_paper":"/paper/2607.06945"},"observation_digest":"sha256:3b5820c18957778402aee7eb5fd777885800a273c4bca2e3aedbf271a50da451","observation_id":"0fdd3840-6276-4b66-8932-954226e4923a","resolution":{"observed_at":"2026-07-09T22:46:35.975773Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2603.24489","snapshot_observed_at":"2026-08-02T02:49:23.888427Z","title":"Model predictive path in- tegral control as preconditioned gradient descent,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.14245","last_updated":"2026-07-15T18:04:38Z","snapshot_observed_at":"2026-08-19T17:54:07.858821Z","submitted_at":"2026-07-15T18:04:38Z","title":"Information-Theoretic Adaptive Cooling for Deterministic MPPI via Entropy Feedback","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T02:49:23.888427Z"},"links":{"cited_paper":"/paper/2603.24489","citing_paper":"/paper/2607.14245"},"observation_digest":"sha256:16a225f762c7b5c82cd2cf8d1f2360c66e26719667c07161c8e3194c54095ed3","observation_id":"83a66a46-2603-4384-a154-21351e301d67","resolution":{"observed_at":"2026-08-02T02:49:23.888427Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2603.24489/citation-record","integrity":"/paper/2603.24489/integrity","json":"/paper/2603.24489/citation-record.json","paper":"/paper/2603.24489"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The cross-entropy method for opti- mization","venue":null,"work_id":"fefc9180-2fcc-4fd5-8db4-9a2425000146","year":2013},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:0e1db69f188d1e0e007bcfe914cc6c7cb2f1eec0a5934bd3e6303d3381337884","observation_id":"1187a7c1-107f-4b01-9e05-5f1958486d2f","resolution":{"observed_at":"2026-05-25T06:50:29.228600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA- ES)","venue":null,"work_id":"fed4dc98-8efc-46db-a944-68c53ddaec7b","year":2003},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:eb2f3aa1286d4dfa04211c387563e4cc0459c00727fa44d1f0af4fb6b7c8ab08","observation_id":"6d5639a6-58fb-4eb3-ac2d-3d8a5a9e72a2","resolution":{"observed_at":"2026-05-25T06:50:29.219647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Optimality and suboptimality of MPPI control in stochastic and deterministic settings","venue":null,"work_id":"40080288-1f74-4a09-803f-039b48341287","year":2025},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:6688a26294577c521f6c76e78ba0cf07291852461448361fbd5eed474e5f2954","observation_id":"4c2420d8-7e08-4201-be26-841b782673dc","resolution":{"observed_at":"2026-05-25T06:50:29.223693Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2511.08019","last_updated":"2026-04-08T07:31:47Z","snapshot_observed_at":"2026-08-19T23:18:03.063301Z","submitted_at":"2025-11-11T09:21:27Z","title":"Model Predictive Control via Probabilistic Inference: A Tutorial and Survey","version":4},"cited_work":{"arxiv_id":"2511.08019","doi":null,"metadata_source":"pith","pith_arxiv_id":"2511.08019","snapshot_observed_at":"2026-07-01T20:26:12.985261Z","title":"Model Predictive Control via Probabilistic Inference: A Tutorial and Survey","venue":"cs.RO","work_id":"5d623843-1db2-4768-a69d-c6e34d8858b8","year":2025},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"cited_paper":"/paper/2511.08019","citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:5ad2995cfdc42d7be6caa498010a39d22f77361f59c70ffb3c269375f75fb5d3","observation_id":"d913fd20-bb54-4fab-821f-7aa35c1a9272","resolution":{"observed_at":"2026-05-25T06:50:27.823740Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.08775","last_updated":"2025-09-11T01:23:12Z","snapshot_observed_at":"2026-08-18T12:58:56.693465Z","submitted_at":"2025-09-10T17:05:16Z","title":"Joint Model-based Model-free Diffusion for Planning with Constraints","version":2},"cited_work":{"arxiv_id":"2509.08775","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2509.08775","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Joint Model-based Model-free Dif- fusion for Planning with Constraints","venue":null,"work_id":"6262240e-6641-472d-9b70-579536e63be3","year":2025},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"cited_paper":"/paper/2509.08775","citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:8d5d250be12b412eea783f37327860335161e5692291c562f4383bc0fd68ab15","observation_id":"4ceaa70f-48a8-4823-a86f-f9eee64464ca","resolution":{"observed_at":"2026-05-25T06:50:27.831979Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.00909","last_updated":"2018-05-20T20:03:59Z","snapshot_observed_at":"2026-08-08T20:31:18.897748Z","submitted_at":"2018-05-02T17:11:20Z","title":"Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review","version":3},"cited_work":{"arxiv_id":"1805.00909","doi":"10.4249/scholarpedia.1658.url:http://www.scholarpedia","metadata_source":"pith","pith_arxiv_id":"1805.00909","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review","venue":"cs.LG","work_id":"e29031ac-37fe-4702-86de-bb869d1f5c9a","year":2018},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"cited_paper":"/paper/1805.00909","citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:65d3b3874111b662b32c677a51042064d2c5e11daae08f5f0829d1ea31124736","observation_id":"400b4931-32cf-4bec-8ce2-c3e9fc4d0d95","resolution":{"observed_at":"2026-05-25T06:50:27.845273Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mir- ror descent search and its acceleration","venue":null,"work_id":"cb69f4f3-1082-4de3-a0b7-b77724406073","year":2018},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:07b76b1637c4f380c74d09a7e8f5bedd7244b59f0e70f46c4a4f1afbea9f0c83","observation_id":"f1807ef8-8577-402a-9476-d2063df8b158","resolution":{"observed_at":"2026-05-25T06:50:29.276926Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Autonomous navigation of agvs in unknown cluttered environments: log- mppi control strategy","venue":null,"work_id":"4acf1ec5-f5bd-4a2e-a736-a6c3ac179b8f","year":2022},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:88bbd5399292368d8778e17cc1a2d167474d7ecdedbaa65306339551b16316af","observation_id":"1d0e46b1-3da8-42b5-bcf2-3fea432e7f8a","resolution":{"observed_at":"2026-05-25T06:50:29.280686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Acceleration of gradient-based path integral method for efficient optimal and inverse optimal control","venue":null,"work_id":"7e9ccff4-bb4d-4832-86b7-6ed86f515a2b","year":2018},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:97e6b1a01ff406b27dd56ce681c752ccb25aaf7f7a981007850d6ba694fd2ca1","observation_id":"5f9a5481-dada-48ef-9027-feaf5cc2e786","resolution":{"observed_at":"2026-05-25T06:50:29.284629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Variational infer- ence mpc for bayesian model-based reinforcement learning","venue":null,"work_id":"42143be8-c99d-48f0-9d1f-5ac3e23fbfc0","year":2020},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:c0b2f128de42d9faea5e8852892fa9f2f9c9509a991932093f6d5b240e808405","observation_id":"27d8577d-8a7d-4613-ad34-01917a1701ea","resolution":{"observed_at":"2026-05-25T06:50:29.288942Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Model-based diffusion for trajectory op- timization","venue":null,"work_id":"a2e7d78b-37d2-4245-8a74-d57ac9b8baaa","year":2024},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:06f42b1156f3649cf6f4de86a95dadd2120d0d729828f12abc58b736192b671e","observation_id":"ff69accb-3757-461a-8e7a-475b5df20fd6","resolution":{"observed_at":"2026-05-25T06:50:29.264303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Re- inforcement learning of motor skills in high dimensions: A path integral approach","venue":null,"work_id":"af85e804-0630-4872-8b1b-d27737c65d93","year":2010},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:b94f3dc01e7d063e98986788ce54627d47e7d8598646d745d0a786705cc2e568","observation_id":"6fa91d3a-4168-405c-a42d-5fe194f99a74","resolution":{"observed_at":"2026-05-25T06:50:29.259993Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1509.01149","last_updated":"2015-10-28T13:23:51Z","snapshot_observed_at":"2026-08-14T22:33:53.863727Z","submitted_at":"2015-09-03T16:18:30Z","title":"Model Predictive Path Integral Control using Covariance Variable Importance Sampling","version":3},"cited_work":{"arxiv_id":"1509.01149","doi":null,"metadata_source":"pith","pith_arxiv_id":"1509.01149","snapshot_observed_at":"2026-07-02T02:06:26.650499Z","title":"Model Predictive Path Integral Control using Covariance Variable Importance Sampling","venue":"cs.SY","work_id":"a4abf5dc-03a0-4314-ba09-57594c0044c6","year":2015},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"cited_paper":"/paper/1509.01149","citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:3e1be6452c2b9865afea907b8f3585ed6874df7389722263395e595315e17718","observation_id":"a253c3ad-05cf-4fab-a799-902fa34aa39d","resolution":{"observed_at":"2026-05-25T06:50:27.838991Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Aggressive driving with model pre- dictive path integral control","venue":null,"work_id":"90b00b50-25c7-4192-bfcd-1f289f6a067a","year":2016},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:3bb569a4d721e0f62d05ec89a26ae9d09b42638823b6d00c2ebca77715ec8ba6","observation_id":"22ab3953-c239-4062-8a39-ebd9d80849e6","resolution":{"observed_at":"2026-05-25T06:50:29.268423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Information theoretic MPC for model- based reinforcement learning","venue":null,"work_id":"0bc340b5-f67f-48a7-941b-deb5f64ebd48","year":2017},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:d81f7ca91af92874f1e328d816f0a6a104e940cf1f59501f789479d579d9daa4","observation_id":"3a8d456f-c002-4d27-ab5d-6efa97ae847b","resolution":{"observed_at":"2026-05-25T06:50:29.253854Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Full-order sampling-based mpc for torque- level locomotion control via diffusion-style annealing","venue":null,"work_id":"5e6c5962-aca5-4348-be83-b3bdaa823013","year":2025},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:f6bbc035ed5420cf21d7306f58942362f78b90b048543391fc6907712510c6a4","observation_id":"e8970203-31e7-48bb-a541-609baa690bfa","resolution":{"observed_at":"2026-05-25T06:50:29.233341Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"CoVO-MPC: Theoretical analysis of sampling- based MPC and optimal covariance design","venue":null,"work_id":"4f5eca73-2a3e-4bdf-a8a1-acbd3254a3ca","year":2024},"citing_paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-25T06:49:16.926107Z"},"links":{"citing_paper":"/paper/2603.24489"},"observation_digest":"sha256:3e5b969ab74a3fc03d1d303c9edc795b70d73660ec5720a4e97487ad3b0c7f9f","observation_id":"5afa638f-1f0d-417d-a5bb-241185a69991","resolution":{"observed_at":"2026-05-25T06:50:29.272721Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2603.24489","last_updated":"2026-05-22T16:53:08Z","latest_version":2,"primary_category":"math.OC","snapshot_observed_at":"2026-07-06T22:50:32.832499Z","submitted_at":"2026-03-25T16:30:05Z","title":"Model Predictive Path Integral Control as Preconditioned Gradient Descent"},"reference_resolution":{"displayed":17,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":4,"verified_fuzzy":13},"total_outbound_references":17},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 3 inbound Pith citation observations for arXiv:2603.24489."}