{"as_of":"2026-08-09T17:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ec277774a1d4caade9c2345063bcbb9e2efc90cca7acd64932e1064e386df0bc","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":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.25388/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":"2026-08-09T04:58:58.359704Z","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:f25186e2a873849cde472463f667451ea8c86962fed5595bd1dd2a96e3639e1a","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":"2026-08-09T04:58:58.359704Z","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":"sha256:637ef7773e41fe7d0cec53316926b99c53bcacad7fc3405bff15dc866dc04298","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":"2026-08-09T04:58:58.359704Z","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":"sha256:58e919af2575e3d068e6d7f3b69be5c76dbea1cb734af0c3ee5a7f8449c6aa45","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":"2026-08-09T04:58:58.359704Z","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":"sha256:01da1f3d6567a4c32efb38b2ea95ce4ba3435b4243c45af558ff50e3aac7a77f","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":"2026-08-09T04:58:58.359704Z","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":"sha256:8acc294339c05f30ce36586077ac654d4915dac64111b83d7a1c0bcead464156","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":"2026-08-09T04:58:58.359704Z","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":"sha256:25366bde08e4cd47b4856f12be12616ba6a4002f60a6ad6af8d64923a3a9d7a5","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":"2026-08-09T04:58:58.359704Z","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":"sha256:975f06026a8b4e196349d4de1abc9013a8e5baeac2d461ccaf75c301df494641","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":"2026-08-09T04:58:58.359704Z","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":"sha256:760687c71de4c958b0a40f4eba94bd2d3de202937624e2813a485116b73db6c5","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":"2026-08-09T04:58:58.359704Z","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":"sha256:8f7e288efc89ba3f0d18794ae2a793554eac3bc710e63f7784423ce09d30d830","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":"2026-08-09T04:58:58.359704Z","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":"sha256:7f7c07f3209796e1805c8a06292478ac3233757546a1ac80b39502f1b3a5ed83","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":"2026-08-09T04:58:58.359704Z","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":"sha256:606a7630b201499730edd79f0791e6ef7d1fd78815fe62d93128cb337cd65d5b","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":"2026-08-09T09:58:26.683562Z","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":"2026-08-09T04:58:58.359704Z","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":"sha256:397b8246663cc0baea91a149e53df05abd84730d2a3778459f6f5e85e8a64aa2","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":"2026-08-09T04:58:58.359704Z","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:a26a0d41883848a4486c5071e652bd099f086c98671efd29945c61922caabacd","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":"2026-08-09T04:58:58.359704Z","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":"sha256:667ce2ff51893ac726a26bab039e6eb5fa24682e364fb8d87003cec2f91eaab3","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":"2026-08-09T04:58:58.359704Z","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":"sha256:8c3509803bf621b81081df78484085b69e6fe59a32c0781af03af177c6d219ff","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":"2026-08-09T04:58:58.359704Z","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":"sha256:6ca6103d2a13c19026c3971417101d0b79e647933b657789b16690f10eff9f74","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":"2026-08-09T04:58:58.359704Z","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":"sha256:6ff2862c17db130bbcaab632acc98af1ac2bdbcc7bfe57b43f7d65afd79920eb","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":"2026-08-09T04:58:58.359704Z","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":"sha256:22726e2eea24ec3fb299129b5c35eee15bf8d1da2b813276fe179617122ee96a","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":"2026-08-09T04:58:58.359704Z","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:ad549e1d21a0a532ad2cb338fdb5b47d49fec138ddb5aab2a0fc5749f6c15b6c","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":"2026-08-09T04:58:58.359704Z","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":"sha256:6a18e49d5769fdcb22008465592a9421ff01f8c8605c48dda050724e2c07c28a","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":"2026-08-09T04:58:58.359704Z","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":"sha256:0e12eb1c99d28fd5c654ad3e6bf7bb94a1c8607af1305353c606db532e7032cd","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":"2026-08-09T04:58:58.359704Z","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:ad8603a5326761bea14314c57cdea9b422cc47063d2012546cd355261626ec4c","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":"2026-08-09T04:58:58.359704Z","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:d2a741a8355dce24039206e4200afb99ee6066e74ac074c305b84edd2d600972","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":"2026-08-09T04:58:58.359704Z","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:fe4a5495f5e395aa2b88425ad493eda42f8e042cf98b99fd8303a790628335f7","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":"2026-08-09T04:58:58.359704Z","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:d17f56623ccc7e4ab32b6ede9c90a7e8ec0bf246611a3ba70ed7a0fc2ac35fa7","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":"2026-08-09T04:58:58.359704Z","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:d3a85671d74bb6de40f73ea3e93280537d8588f1c6f431d44068b9661cc51160","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":"2026-08-09T04:58:58.359704Z","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:b4a5fd9509233882978c5b14c60b5e7642703a3aa4165d879e531fdba99ce8bb","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":"2026-08-09T04:58:58.359704Z","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":"sha256:12d20c07ca3d15dd987fb9d9dd88e1d64fb2768c3052430bd56b46853f907894","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":"2026-08-09T04:58:58.359704Z","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":"sha256:5fa404a1693c1bde0faa3dd302e72cea07193633233e1af3e56453b99c820aa1","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":"2026-08-09T04:58:58.359704Z","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":"sha256:3c24217499becd0d62e186673b7ef3f06854e9177f4e66eb3dfe535402653aa7","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":"2026-08-09T04:58:58.359704Z","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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2607.25388."}