{"as_of":"2026-08-10T18:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:da0fc5f46a6a64a0d179c989015961c4afc44b82b43c95cfa80ebb8817b0f557","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-28T08:42:38.352002Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2606.04123/citation-record","integrity":"/paper/2606.04123/integrity","json":"/paper/2606.04123/citation-record.json","paper":"/paper/2606.04123"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Cambridge university press, 2004","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:adc39a4fbc93ae96106b57f42aa7e27656aac2c283651663e9429fede279b1cd","observation_id":"dbaa3724-e8d7-4121-80ee-8e8aa75a379a","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Nl2tl: Transforming natural languages to temporal log- ics using large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:354efb7cc2dd29bb02dbfdeb5402636767424dae46c8be691cf5b810ed4418a7","observation_id":"075b45e1-aaf5-4dac-8e1b-9dbf17a4a729","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Chernick.Optimal Impulsive Control of Spacecraft Rel- ative Motion","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:bc16f7ab951dd9fc47ee12ace7652bcbb7bc263e2f9bb9e7596185ac42065a9b","observation_id":"7b5510af-1b12-4ab0-9b12-0ec024042a1d","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"D’Amico.Autonomous Formation Flying in Low Earth Orbit.PhD Thesis, Delft University, 2010","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:29c93057c6f64251b48d628c26b7caf60313d0a22ab9281ca676581b0ab96ec4","observation_id":"a45a0150-ea12-485d-a9eb-b74b58903a7f","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Cvxpy: A python- embedded modeling language for convex optimization.Jour- nal of Machine Learning Research, 17(83):1–5, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:0ae9bb8257a2db983e52bba96cd4759c5bc289206e808e86a8d888ba93a2d30c","observation_id":"f6a12086-0eb0-4ae1-a1b8-03b808b4869e","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Ecos: An socp solver for embedded systems","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:550eb24bc9b8f33be35fb5941f240cba5fcd0c00e71b6138e8cb7e52577a068b","observation_id":"4f5b3c34-aa13-4255-9110-dd7476714928","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"An optimal guidance law for planetary landing","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:49ed2903ecbb5a57c64d2f49463a618b758803dd821882cb7cbe2623bb000146","observation_id":"6416187f-bcf6-4ef6-8c89-cdb6cede2e1c","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Foundation models in robotics: Applications, challenges, and the future.The International Journal of Robotics Research, 44(5):701–739,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:c41d5b2cff0ef88a6adacff35f8e17c77f49ee155268b72d77a31592c144f368","observation_id":"45c39cf7-8466-46bd-91b9-8b558b68dbcd","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Space-llava: A vision-language model adapted to extraterrestrial applications","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:dec397c471fd1519cf6ef0daf0624c3db7366bcbc92851a806a14dcf55d64423","observation_id":"3fdfe141-d7fb-44a6-bddf-f1dec67f434f","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Transformers for trajectory optimiza- tion with application to spacecraft rendezvous","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:de1a9a1ff1343900c241b756cdb5633bd1c9ffd458fffef79a956d8610c9dcee","observation_id":"15f14362-957c-4e7f-b79a-b82cf7654cac","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Deep reinforcement learn- ing for spacecraft proximity operations guidance.Journal of Spacecraft and Rockets, 58(2):254–264, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:1d548cbf6d0c0dcb3d2bbee12baac65c4558816d106d215231b08edcf194552d","observation_id":"dbe5fe89-f637-4354-aa50-59a890db0ae3","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","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":"2601.04334","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T03:59:32.689300Z","title":"Autonomous reasoning for spacecraft control: A large language model framework with group relative policy optimization","venue":null,"work_id":"b8ece347-60e4-4ed7-8167-6d9894480823","year":2026},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:c92b11740ab6c57883a02da3f8f745dbc576287fe054c84c93953f8e327509d6","observation_id":"c5f83316-ba3c-4aa9-a8c4-e82e5dec1356","resolution":{"observed_at":"2026-07-02T04:56:39.140788Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.02029","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-02T04:56:39.129673Z","title":"Canonical intermediate representation for llm-based optimization problem formulation and code generation","venue":null,"work_id":"6344f90f-e75d-4635-9f2a-085b0e7624e9","year":2026},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:fdff4b59d7d92f3b527f2254e9f728df1513874610b6a483456cfed736dcf817","observation_id":"048fb448-6a01-4775-80fb-d2971a6b42b5","resolution":{"observed_at":"2026-07-02T04:56:39.131784Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.17334","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-02T04:56:39.132867Z","title":"URL https://arxiv.org/abs/2512","venue":null,"work_id":"798b6642-e0a7-4733-be91-69e702bb2295","year":2025},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:7d5464b1cf612a94a5c496082b08f8226b7db2022768420a4afbf7468e19d963","observation_id":"ccd2c3c1-dc0f-4392-acfb-e329466633c1","resolution":{"observed_at":"2026-07-02T04:56:39.134738Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Fast homotopy for spacecraft rendezvous trajectory optimization with discrete logic.Journal of Guidance, Control, and Dynamics, 46(7): 1262–1279, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:21105b75515bd498d35ba08d27b2cd5530734726e659aa46fb5c775ab812f369","observation_id":"5d32d997-3ba5-424b-8b85-0b9fe1301820","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Malyuta, T","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:3b07e676187db891984bfe156af5a2608398fd1d6a08877f5ce55a647c7da09c","observation_id":"b5d24ae0-c405-4212-8734-b5e735b5e273","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","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":"2601.04789","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-02T04:56:39.136139Z","title":"Nc2c: Au- tomated convexification of generic non-convex optimization problems.arXiv preprint arXiv:2601.04789, 2026","venue":null,"work_id":"79abc47a-e0e0-486a-810c-0c20433fe0c3","year":2026},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:ee86df7ad6c8b35c5f52cebae0e5224e2f19b0353c97c91fbc80978eb6b22ebd","observation_id":"a1d78386-d74c-4e29-b76a-42d78be4edbb","resolution":{"observed_at":"2026-07-02T04:56:39.137967Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Nl4opt competition: Formulating optimiza- tion problems based on their natural language descriptions","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:c395d8bafe06d08116574f3a479a6c90720b1b67e06aa0d701f9c935d23aacef","observation_id":"b458149b-2e48-4f33-8cd8-5022c0235ffe","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:072580cd795e2cdf2be4f9ea4069e9af85e9017e225d94a84fa81e22dd31033a","observation_id":"2de3b17c-c7be-491b-8ffa-04973acaced2","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Towards robust spacecraft trajectory optimization via transformers","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:cfcc65c4a0942146fb331ca4d1d45510b9f94a0a1dd6f77da0e8ae7f9700e9de","observation_id":"bee19eac-d5c3-4569-9dc8-8a88dffe1b07","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Pabon, Daniele Gammelli, Marco Pavone, and Simone D’Amico","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:3e14c6efbffab057025271c040629c988f01035c5b830c685dceced7b265792f","observation_id":"98d2ab24-420e-4838-90e5-ffc56b3e6347","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09536","last_updated":"2025-03-06T19:37:39Z","snapshot_observed_at":"2026-08-09T20:14:21.612863Z","submitted_at":"2024-09-14T21:36:22Z","title":"VernaCopter: Disambiguated Natural-Language-Driven Robot via Formal Specifications","version":2},"cited_work":{"arxiv_id":"2409.09536","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.09536","snapshot_observed_at":"2026-07-02T04:56:39.129477Z","title":"Vernacopter: Disambiguated natural- language-driven robot via formal specifications.arXiv preprint arXiv:2409.09536, 2024","venue":null,"work_id":"f1f02d84-3d6f-4f72-8748-184a45ee23df","year":2024},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"cited_paper":"/paper/2409.09536","citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:f53eb538da6db8f238319147b539dfabcfbaac49091a6f2c1ce0e8619c95502e","observation_id":"b2344711-7ffa-49e3-a3cf-e6e8c68a27c1","resolution":{"observed_at":"2026-07-02T04:56:39.131645Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Chatstl: A frame- work of translation from natural language to signal temporal logic specifications for autonomous vehicle navigation out of blocked scenarios","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:8f9a7f51fb44745aa6c582d6b7a4aca820d18900eafad8e0d2d433c89af904c8","observation_id":"97cfcc16-60be-48bc-a8d9-36b823557f0d","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Plug in the safety chip: Enforcing constraints for llm- driven robot agents","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:1ba7cb7d309a1159a4fe0e99c1aeca51c98c346c3c3d6afb233ecd5b0f306873","observation_id":"b1fa3972-e6ca-435f-8b07-910fdad72147","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"You will take in 2 files:","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:2fdcf3e9131c08021a98de6e9e9f88e59f6ed48aa508fb72d12624c3a0f18dc1","observation_id":"0ec9caf6-ec47-441f-ad3d-77a6c6271a3c","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:5d354e290d0d37cbc1d1556424ca4a2ec5a5c677d90a25917d283796ef0a575e","observation_id":"a595fa37-305c-4fa2-97e5-515010da870a","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:28ab26931ac55ce3ebb085f062f5de29b85727fdb4a3c93702619d27887fa541","observation_id":"034f9d9e-0074-46f3-a5e6-0e37dad71077","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-28T08:42:38.352002Z","title":"Generated LATEX Output for Prompt 1 Observation Distance Constraint Letd max = 30m be the maximum allowable relative posi- tion norm for observation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-28T08:42:38.352002Z"},"links":{"citing_paper":"/paper/2606.04123"},"observation_digest":"sha256:f8dea58501617077383ead5d3b9416a30a940ca0c969122a73ffae17afd917fd","observation_id":"47cf6ba2-d97a-4dea-9f06-8abca213ae2c","resolution":{"observed_at":"2026-06-28T08:42:38.352002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.04123","last_updated":"2026-06-02T18:33:38Z","latest_version":1,"primary_category":"math.OC","snapshot_observed_at":"2026-08-03T21:39:56.590668Z","submitted_at":"2026-06-02T18:33:38Z","title":"Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":23,"verified_exact":5,"verified_fuzzy":0},"total_outbound_references":28},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2606.04123."}