{"as_of":"2026-08-08T17:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:273b46d93f6d66a642c5de66ccc4f1ba730182ad7bad5e35d7a62411a1197592","coverage":[{"denominator":30,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":30,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T02:39:01.527051Z","state":"measured"},{"denominator":30,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":30,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2607.25388/citation-record","integrity":"/paper/2607.25388/integrity","json":"/paper/2607.25388/citation-record.json","paper":"/paper/2607.25388"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:39:01.396381Z","title":"Autonomous vehicles on the edge: A survey on autonomous vehicle racing,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.396381Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:696a923a09a83ac90049fcab3cb525ce66fd226a23137acb6b2e0d5c34f6360d","observation_id":"c02ce72b-abbb-4f45-8cdd-19715da8698b","resolution":{"observed_at":"2026-08-01T02:39:01.396381Z","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":"2026-08-01T02:39:01.401453Z","title":"Forzaeth race stack—scaled autonomous head-to-head racing on fully commercial off-the-shelf hardware,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.401453Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:08f3636c76509079af3c80c5094e65772f058767b32e870632fb266d08da2349","observation_id":"38fdbf7b-78db-442a-99ef-8b9e1588a7de","resolution":{"observed_at":"2026-08-01T02:39:01.401453Z","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":"2026-08-01T02:39:01.405872Z","title":"Modular decision-making and drivable areas for multi-agent autonomous racing,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.405872Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:475664a3521edb229889d8296bb7c05be5d503dcbffdae5d3f1936bd7b0602d8","observation_id":"b7acdb72-0abe-494a-b6c2-480dcf846024","resolution":{"observed_at":"2026-08-01T02:39:01.405872Z","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":"2026-08-01T02:39:01.410476Z","title":"Optimization-based au- tonomous racing of 1: 43 scale rc cars,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.410476Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:ec32a7fe564bd6b69d94e6515fd03b634df7308ba1d8adce722c798bba23da5a","observation_id":"4a086adc-9d05-4291-a081-9eedd6ecacac","resolution":{"observed_at":"2026-08-01T02:39:01.410476Z","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":"2026-08-01T02:39:01.415139Z","title":"Reduce lap time for autonomous racing with curvature-integrated mpcc local trajectory planning method,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.415139Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:532a88cf038b70e62486b0fa99180a2e2be78ef2fef396ad0b5e112b4695a7e8","observation_id":"7b6a3507-2d11-4f37-84cb-287766a34aba","resolution":{"observed_at":"2026-08-01T02:39:01.415139Z","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":"2026-08-01T02:39:01.419704Z","title":"A data-driven aggressive autonomous racing framework utilizing local trajectory planning with velocity prediction,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.419704Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:1037663a3ae8c79b02d5d7ebf4cac20c9ddc7351639d1b54250d689d173e25b0","observation_id":"3669452b-5e3d-425f-94e5-5c54f195c7be","resolution":{"observed_at":"2026-08-01T02:39:01.419704Z","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":"2026-08-01T02:39:01.424643Z","title":"Kineto-dynamical planning and accurate execution of minimum-time maneuvers on three-dimensional circuits,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.424643Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:82070f2f48e0dc944e56d09c4ddf03db59db0b29a43e095c9c95c77d5b2a760a","observation_id":"5aeefff9-4d00-4d44-8154-125d0609f273","resolution":{"observed_at":"2026-08-01T02:39:01.424643Z","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":"2026-08-01T02:39:01.428758Z","title":"A multi-stage time-variant motion planner for agile autonomous driving maneuvers,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.428758Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:da3a94516f5402bc1a169744533200d545ed9cb75b934b217310903fe003915f","observation_id":"57561530-fa43-4090-88b8-1517b923a8d8","resolution":{"observed_at":"2026-08-01T02:39:01.428758Z","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":"2026-08-01T02:39:01.433110Z","title":"End2race: Efficient end- to-end imitation learning for real-time f1tenth racing,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.433110Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:d87c736a1b16cab31368b1fa11e25e75dbc183ac9d60c18fc807ff4b65c5fc24","observation_id":"069b951e-d457-4eb2-b88f-d57e1c18b19c","resolution":{"observed_at":"2026-08-01T02:39:01.433110Z","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":"2026-08-01T02:39:01.438298Z","title":"Flow matching-based autonomous driving planning with advanced interactive behavior modeling,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.438298Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:6ddfcdc5d07c11debf58316cf38482397b534def8483970c178fe907a99a2649","observation_id":"53196fd7-2b71-4147-a5db-067592f97964","resolution":{"observed_at":"2026-08-01T02:39:01.438298Z","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":"2026-08-01T02:39:01.442451Z","title":"Diffusion-based planning for autonomous driving with flexible guidance,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.442451Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:ea305e664cece4e582f5bd3957f3ec4f5be5e479b7d1133e72b10270ea17a8eb","observation_id":"8aaaec5f-2149-400b-93e6-0e556971f9a5","resolution":{"observed_at":"2026-08-01T02:39:01.442451Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.04384","last_updated":"2026-07-20T13:35:34Z","snapshot_observed_at":"2026-08-08T13:14:07.563570Z","submitted_at":"2025-07-06T13:14:35Z","title":"Rapid and Safe Trajectory Planning over Diverse Scenes through Diffusion Composition","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.04384","snapshot_observed_at":"2026-08-01T02:39:01.446803Z","title":"Rapid and safe trajectory planning over diverse scenes through diffusion composition,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.446803Z"},"links":{"cited_paper":"/paper/2507.04384","citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:82125c3791226cddc538b0ee83fa3cdd461a0cf78ff6b394d28d6acae5061919","observation_id":"58347937-91c0-47bb-8971-092eecb70697","resolution":{"observed_at":"2026-08-01T02:39:01.446803Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2602.06925","last_updated":"2026-07-21T13:01:24Z","snapshot_observed_at":"2026-08-06T05:43:13.949540Z","submitted_at":"2026-02-06T18:20:13Z","title":"Strategizing at Speed: A Learned Model Predictive Game for Multi-Agent Drone Racing","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2602.06925","snapshot_observed_at":"2026-08-01T02:39:01.451415Z","title":"Strategizing at speed: A learned model predictive game for multi-agent drone racing,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.451415Z"},"links":{"cited_paper":"/paper/2602.06925","citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:ea546f61a75e22a9690aeedf079d0f7a6d79a3b8cbb8bdc74216971b6328cb16","observation_id":"99dfbc22-f905-4f00-96fd-86775a3abcad","resolution":{"observed_at":"2026-08-01T02:39:01.451415Z","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":"2026-08-01T02:39:01.455767Z","title":"α-racer: Real-time algorithm for game-theoretic motion planning and control in autonomous racing using near-potential function,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.455767Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:2692aa922a5beab5a859bfd825a44121346052180c4759db3f96fbcac44fd77b","observation_id":"ba2157db-e387-4cdf-83d7-27d9a667cfa8","resolution":{"observed_at":"2026-08-01T02:39:01.455767Z","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":"2026-08-01T02:39:01.459865Z","title":"Learning two-agent motion planning strategies from generalized nash equilibrium for model predictive control,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.459865Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:6c205ee45115b804aba38707db9e4b938bcff435fb74e51db66f01fcc6ebd3b5","observation_id":"9c3223c4-bbbd-42b2-aee3-55e91fa80fc0","resolution":{"observed_at":"2026-08-01T02:39:01.459865Z","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":"2026-08-01T02:39:01.464231Z","title":"Driving is a game: Combining planning and prediction with bayesian iterative best response,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.464231Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:d21513ddb28e54613d567cee0684fa867fc01950d85529434223c6c36a9f753f","observation_id":"0e1b860c-08e1-4593-8460-db8a541d262a","resolution":{"observed_at":"2026-08-01T02:39:01.464231Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.20203","last_updated":"2025-08-27T18:30:28Z","snapshot_observed_at":"2026-08-05T15:18:15.327017Z","submitted_at":"2025-08-27T18:30:28Z","title":"Regulation-Aware Game-Theoretic Motion Planning for Autonomous Racing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.20203","snapshot_observed_at":"2026-08-01T02:39:01.468584Z","title":"Regulation-aware game-theoretic motion planning for autonomous racing,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.468584Z"},"links":{"cited_paper":"/paper/2508.20203","citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:32f8dbb88e0b580ec3e0cb0292248a27033c61d132af440e14bbc6fc09f424b9","observation_id":"32bc262d-d17f-4505-8054-89410e5a3d53","resolution":{"observed_at":"2026-08-01T02:39:01.468584Z","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":"2026-08-01T02:39:01.473339Z","title":"A sequential quadratic programming approach to the solution of open-loop generalized nash equilibria,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.473339Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:aef27309e1466117c222752b145ec59710b1046bdca8d2aaebfd92606a1e85c4","observation_id":"ad04c559-4beb-4870-846d-455d96048d8e","resolution":{"observed_at":"2026-08-01T02:39:01.473339Z","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":"2026-08-01T02:39:01.477826Z","title":"A real-time game theoretic planner for autonomous two-player drone racing,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.477826Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:a53c3905f932c697eb120e9ce055850e4a768dddcde123ba5795de6f0b6ab75b","observation_id":"1cb93a97-032e-4543-a21d-456aefc9661b","resolution":{"observed_at":"2026-08-01T02:39:01.477826Z","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":"2026-08-01T02:39:01.482210Z","title":"Game- theoretic planning for self-driving cars in multivehicle competitive scenarios,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.482210Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:e3c9a1947a48aa1a629cf2fce55a407e39a93b99cdfc1b9541de200277692899","observation_id":"d10916de-9d82-48e7-b101-90b10d9922b5","resolution":{"observed_at":"2026-08-01T02:39:01.482210Z","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":"2026-08-01T02:39:01.486359Z","title":"A rapid iterative trajectory planning method for automated parking through differential flatness,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.486359Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:5a3356875e830332dcb697f68009fda907f60dfc1684ff14877feaac8fc6c98e","observation_id":"92e159c6-7e03-4d67-bc1b-2b00d2f284ce","resolution":{"observed_at":"2026-08-01T02:39:01.486359Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.08019","last_updated":"2026-04-08T07:31:47Z","snapshot_observed_at":"2026-07-06T22:35:27.050353Z","submitted_at":"2025-11-11T09:21:27Z","title":"Model Predictive Control via Probabilistic Inference: A Tutorial and Survey","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.08019","snapshot_observed_at":"2026-08-01T02:39:01.490913Z","title":"Model predictive control via probabilistic inference: A tutorial,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.490913Z"},"links":{"cited_paper":"/paper/2511.08019","citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:179b79b3234d3a52ba2f083643905c611c6ee319950072d9a6d914ebac86f38d","observation_id":"236dcd3c-589a-4b5f-bb91-8322151939a9","resolution":{"observed_at":"2026-08-01T02:39:01.490913Z","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":"2026-08-01T02:39:01.495515Z","title":"Biased-mppi: Informing sampling- based model predictive control by fusing ancillary controllers,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.495515Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:a0bad6b8ce684408f732a86a94d31dbd59483be09de963a1d71cce1f610574c4","observation_id":"49b60087-eadf-4e3b-9995-1faeafa0ff34","resolution":{"observed_at":"2026-08-01T02:39:01.495515Z","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":"2026-08-01T02:39:01.499983Z","title":"Stein variational guided model predictive path integral control: Proposal and experiments with fast maneuvering vehicles,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.499983Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:829c232317ba48d6c46618692c7d8d316eb6700ddd46ab0ab7e8871053e04877","observation_id":"80f42c14-7600-4eef-9b5d-71e36356a724","resolution":{"observed_at":"2026-08-01T02:39:01.499983Z","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":"2026-08-01T02:39:01.504310Z","title":"The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles?","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.504310Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:b72d5a4dd90791dca52058dceb79fdb79f0252080416bf99d50e0c4a1f5d0096","observation_id":"be273c67-8492-45eb-a1e0-989855013897","resolution":{"observed_at":"2026-08-01T02:39:01.504310Z","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":"2026-08-01T02:39:01.508693Z","title":"Minimum curvature trajectory planning and control for an autonomous race car,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.508693Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:4d4d492b1e4e635a1bf0650e39d017043328dc6a791d0918d2dc21b4c83522c3","observation_id":"9514962b-d781-4405-ab21-75720c8e18f3","resolution":{"observed_at":"2026-08-01T02:39:01.508693Z","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":"2026-08-01T02:39:01.513064Z","title":"Motion plan- ning for autonomous driving with a conformal spatiotemporal lattice,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.513064Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:a78b41d61fba7000b426555305243a640a88cfcfbc454f45a147da51aa341903","observation_id":"d77cb12b-6fc8-4448-8792-ea37ae439200","resolution":{"observed_at":"2026-08-01T02:39:01.513064Z","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":"2026-08-01T02:39:01.517693Z","title":"Evo-mpcc: Enhanced velocity optimization with learning-based auto-tuning for real-time vehicle trajectory planning,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.517693Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:aa30116cfdae19a970f90c80991e4bf806b9a70ba6bf5258b7118dbe9c115e27","observation_id":"cbb0e1cc-5d6e-4a80-8825-077f7c1366fa","resolution":{"observed_at":"2026-08-01T02:39:01.517693Z","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":"2026-08-01T02:39:01.522015Z","title":"CasADi – A software framework for nonlinear optimization and opti- mal control,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.522015Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:a402b73545b067eca52ae10d18d95159ab4c2fa99acc58895a25c714dd52e14c","observation_id":"b04d09d0-4467-479e-a5dd-c67d93af229a","resolution":{"observed_at":"2026-08-01T02:39:01.522015Z","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":"2026-08-01T02:39:01.527051Z","title":"On adversarial robustness of trajectory prediction for autonomous vehicles,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T02:39:01.527051Z"},"links":{"citing_paper":"/paper/2607.25388"},"observation_digest":"sha256:abd61e4903e3cc72526682ae18446dc7a6ab43ce3a2fd430178353890adcda99","observation_id":"07c76bc0-7f32-42ac-9289-be9d02d076c6","resolution":{"observed_at":"2026-08-01T02:39:01.527051Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.25388","last_updated":"2026-07-28T07:46:43Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-07T00:17:06.132579Z","submitted_at":"2026-07-28T07:46:43Z","title":"SGTP: Sampling-based Game-Theoretic Planning for Real-Time Multi-Vehicle Autonomous Racing"},"reference_resolution":{"displayed":30,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":30,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":30},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2607.25388."}