{"as_of":"2026-08-07T22:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1585ac040883a47420fac3acb199fb43e34f61b438810eb55f87dc86d38ca8ba","coverage":[{"denominator":60,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":60,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:13:45.072007Z","state":"measured"},{"denominator":60,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":60,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2505.15793/citation-record","integrity":"/paper/2505.15793/integrity","json":"/paper/2505.15793/citation-record.json","paper":"/paper/2505.15793"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:51.140424Z","title":"Reinforcement learning algorithms: A brief survey","venue":null,"work_id":"0c27afdd-4fd6-4a2d-9e08-cc7ad63691dd","year":2023},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:38.007767Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:429375358e12d9a7519cfddb2842ccdc36b6369c4afba6976fc7a8b7341169df","observation_id":"ff2bf7b7-d52d-45aa-9f95-9e1c3d040280","resolution":{"observed_at":"2026-08-07T15:13:51.245923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T15:13:38.089874Z","title":"Deep reinforcement learning: A survey","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:38.089874Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:e3ada278dfe649d82110c5193c2ec89b3e4a1720f02023eec474036fc017d130","observation_id":"ee4e5cd9-eb1f-478a-a4fa-e22e84b9b71e","resolution":{"observed_at":"2026-08-07T15:13:38.089874Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.10330","last_updated":"2024-05-24T22:33:04Z","snapshot_observed_at":"2026-08-04T09:15:33.903637Z","submitted_at":"2022-05-20T17:42:38Z","title":"A Review of Safe Reinforcement Learning: Methods, Theory and Applications","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.10330","snapshot_observed_at":"2026-08-07T15:13:38.190951Z","title":"A review of safe reinforcement learning: Methods, theory and applications","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:38.190951Z"},"links":{"cited_paper":"/paper/2205.10330","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:84fa5fc6c40a73cf74c3cb0286a87742d659f6c7325bc329c3d243c31563106d","observation_id":"dd28ad47-5f5d-446c-9af6-b2b9d975e6f5","resolution":{"observed_at":"2026-08-07T15:13:38.190951Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:50.865566Z","title":"Milestones in autonomous driving and intelligent vehicles: Survey of surveys","venue":null,"work_id":"2e01efad-c911-4a77-9c5f-052fdc6ac40a","year":2022},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:38.291323Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:f8ff7e25ea3e35ed771a62532069b2d61ea12c29539df8f568f3a97f96f0194d","observation_id":"d2fb4b9c-c9e0-4703-89e4-3e604ed0c6d0","resolution":{"observed_at":"2026-08-07T15:13:50.991617Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:50.569500Z","title":"Event-triggered model predictive control with deep reinforcement learning for autonomous driving","venue":null,"work_id":"b1506262-3353-44d7-8840-0b0a2ba88f15","year":2023},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:38.501592Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:9aa38020a31433e633019a08d49a254e87d847ed8bcaab50ff9d8179d5f4a15a","observation_id":"09ea864e-390f-4e7d-a28e-99d38fa1a72d","resolution":{"observed_at":"2026-08-07T15:13:50.702190Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:50.413450Z","title":"Deep reinforcement learning with nmpc assistance nash switching for urban autonomous driving","venue":null,"work_id":"9c43a3ff-fbb3-4daa-b249-0e1e991ff85f","year":2022},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:38.617508Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:5292595e088eed10fcbd4eed691bcb4ddaaa3a2804536d260b1dcd332dbe371c","observation_id":"4d6fcc8d-e843-4e4e-af27-db0d689266da","resolution":{"observed_at":"2026-08-07T15:13:50.508191Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T15:13:38.717304Z","title":"Language models are few-shot learners","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:38.717304Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:05c561c971637143dcac85ed544031279e0bd3c5333f4daa225ec9a748fda68d","observation_id":"f3defba4-44d7-4ada-9197-f848bd7dcbc0","resolution":{"observed_at":"2026-08-07T15:13:38.717304Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-07T15:13:38.938324Z","title":"Llama: Open and efficient foundation language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:38.938324Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:4e89d8766b9b67d4e99b7930cc010cf42a6cefb6d8af4be6e5da8038e1069e47","observation_id":"0275447b-62ec-49de-8395-410dab057a5e","resolution":{"observed_at":"2026-08-07T15:13:38.938324Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.02361","last_updated":"2019-06-06T00:02:37Z","snapshot_observed_at":"2026-08-07T09:27:07.685326Z","submitted_at":"2019-06-06T00:02:37Z","title":"Explain Yourself! Leveraging Language Models for Commonsense Reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.02361","snapshot_observed_at":"2026-08-07T15:13:39.086618Z","title":"Explain yourself! leveraging language models for commonsense reasoning","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:39.086618Z"},"links":{"cited_paper":"/paper/1906.02361","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:d9e9e589a8297567d72a093d6f3a3a23e3494125a3223e240a0fb8e0c199e731","observation_id":"b8f3bdbb-7e1e-4f7f-a01c-f7b19cb183a8","resolution":{"observed_at":"2026-08-07T15:13:39.086618Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.11207","last_updated":"2023-10-17T12:34:32Z","snapshot_observed_at":"2026-08-07T08:04:01.104100Z","submitted_at":"2023-10-17T12:34:32Z","title":"Can Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.11207","snapshot_observed_at":"2026-08-07T15:13:39.160195Z","title":"Can large language models explain themselves? a study of llm-generated self-explanations","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:39.160195Z"},"links":{"cited_paper":"/paper/2310.11207","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:af57476043d3ec2c8e81d6289aa426a3ba3cba5d85d7a9636a6c9c9840b55892","observation_id":"f7eb0243-a63e-4bfe-9e2b-a2af77a3eb0a","resolution":{"observed_at":"2026-08-07T15:13:39.160195Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-07T15:13:39.232635Z","title":"The llama 3 herd of models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:39.232635Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:1ffa3eb611de2a74cd546187999f97b249124d53262130807bd8d32313d4be8a","observation_id":"bce1d8a1-66bd-4254-8282-05cb920efc09","resolution":{"observed_at":"2026-08-07T15:13:39.232635Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02954","last_updated":"2024-01-05T18:59:13Z","snapshot_observed_at":"2026-08-02T13:11:16.882565Z","submitted_at":"2024-01-05T18:59:13Z","title":"DeepSeek LLM: Scaling Open-Source Language Models with Longtermism","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02954","snapshot_observed_at":"2026-08-07T15:13:39.381567Z","title":"Deepseek llm: Scaling open-source language models with longtermism","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:39.381567Z"},"links":{"cited_paper":"/paper/2401.02954","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:d5d164a713ea58a9efb4b5ba8422c0a23440d888939c2de4ffb8c791883ab7a4","observation_id":"4ee9c737-24d7-4521-a350-52090cc44a5a","resolution":{"observed_at":"2026-08-07T15:13:39.381567Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-07T15:13:39.513175Z","title":"Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:39.513175Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:867eca5b32336c4458cb01998e535d7206e5c8960669904559a309db4786f00a","observation_id":"78af3939-c290-4f45-b8ad-fafe89bd5cda","resolution":{"observed_at":"2026-08-07T15:13:39.513175Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:50.232698Z","title":"Limsim++: A closed-loop platform for deploying multimodal llms in autonomous driving","venue":null,"work_id":"e746ae10-96df-43d9-bb9f-8a043027b41f","year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:39.649174Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:680ff4236cea7040880dc46fe55ff0398d5b630565e59708f12e7ed8fd878a9a","observation_id":"55b60325-e9b7-4c16-a5ea-122aa48d87cf","resolution":{"observed_at":"2026-08-07T15:13:50.317088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:50.029608Z","title":"Lampilot: An open benchmark dataset for autonomous driving with language model programs","venue":null,"work_id":"516d451c-17a0-492a-af8f-404217eb1cd3","year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:39.724284Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:a683a789248e4ab8e0c66a8db9dbcb547c4305684e00ef8ce24b21fca6c2348a","observation_id":"88f47f00-536c-4284-ba38-83acc0b6a09d","resolution":{"observed_at":"2026-08-07T15:13:50.125958Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00415","last_updated":"2024-08-01T09:32:01Z","snapshot_observed_at":"2026-08-04T00:13:16.751984Z","submitted_at":"2024-08-01T09:32:01Z","title":"DriveArena: A Closed-loop Generative Simulation Platform for Autonomous Driving","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00415","snapshot_observed_at":"2026-08-07T15:13:39.870729Z","title":"Drivearena: A closed-loop generative simulation platform for autonomous driving","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:39.870729Z"},"links":{"cited_paper":"/paper/2408.00415","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:3f7fa899b9dd851e37665f317fdfa8ed5ced6fdb0875a474efe11b278339a6ee","observation_id":"2b00062c-5c10-4411-b073-9d8a3d1485ca","resolution":{"observed_at":"2026-08-07T15:13:39.870729Z","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":"2026-08-07T15:13:40.028157Z","title":"Driving with llms: Fusing object-level vector modality for explainable autonomous driving","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:40.028157Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:35f74dac7df0ee5d9626b4176492765d46d07715adceff20ad4ff9e0c97a38df","observation_id":"a137705b-f166-4471-b83e-099d205cdab0","resolution":{"observed_at":"2026-08-07T15:13:40.028157Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.01043","last_updated":"2024-08-12T11:53:28Z","snapshot_observed_at":"2026-07-06T16:42:04.139453Z","submitted_at":"2023-11-02T07:23:33Z","title":"LLM4Drive: A Survey of Large Language Models for Autonomous Driving","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.01043","snapshot_observed_at":"2026-08-07T15:13:40.153066Z","title":"Llm4drive: A survey of large language models for autonomous driving","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:40.153066Z"},"links":{"cited_paper":"/paper/2311.01043","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:981c27daebdf1c36cf8d50be663ada3da8d50109439e32b1bbf7d4b8b503ee64","observation_id":"dedc060e-f68f-46ea-a839-b7e2bbb88b15","resolution":{"observed_at":"2026-08-07T15:13:40.153066Z","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":"2026-08-07T15:13:40.272522Z","title":"Survey on large language model-enhanced reinforcement learning: Concept, taxonomy, and methods","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:40.272522Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:7dbdb70dd6c5502b4023008ca0f011d997b1f767c35f3306bd31dfe812290872","observation_id":"28a9d241-289f-4a2c-987c-3e51f00bef1a","resolution":{"observed_at":"2026-08-07T15:13:40.272522Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.15214","last_updated":"2025-02-21T05:01:30Z","snapshot_observed_at":"2026-08-07T17:59:51.255537Z","submitted_at":"2025-02-21T05:01:30Z","title":"The Evolving Landscape of LLM- and VLM-Integrated Reinforcement Learning","version":1},"cited_work":{"arxiv_id":"2502.15214","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.15214","snapshot_observed_at":"2026-08-07T15:13:46.454609Z","title":"The Evolving Landscape of LLM- and VLM-Integrated Reinforcement Learning","venue":"cs.LG","work_id":"c7fcb0be-d127-40d9-b293-0b9c03513443","year":2025},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:40.383369Z"},"links":{"cited_paper":"/paper/2502.15214","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:97da51788c3ad020892564dc379eb1a7ca1708acabf7515dcab85c3586ab7cd2","observation_id":"bbb02410-a701-4f50-8c2a-5f685df8c4e4","resolution":{"observed_at":"2026-08-07T15:13:46.682510Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12568","last_updated":"2024-10-20T04:35:34Z","snapshot_observed_at":"2026-08-04T01:53:49.863765Z","submitted_at":"2024-10-16T13:43:00Z","title":"Robust RL with LLM-Driven Data Synthesis and Policy Adaptation for Autonomous Driving","version":2},"cited_work":{"arxiv_id":"2410.12568","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.12568","snapshot_observed_at":"2026-08-07T15:13:46.216829Z","title":"Robust RL with LLM-Driven Data Synthesis and Policy Adaptation for Autonomous Driving","venue":"cs.RO","work_id":"facc4538-540e-4dbf-931b-1ff47020a4fe","year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:40.499557Z"},"links":{"cited_paper":"/paper/2410.12568","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:6b6ac8ec438afc40e7dd11f0ba78ee09243d7a6e49a79ae04d5927e80e73aa9b","observation_id":"8bb67715-276b-401c-8a10-4e6772e4e2ac","resolution":{"observed_at":"2026-08-07T15:13:46.325224Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.13547","last_updated":"2024-05-22T11:32:37Z","snapshot_observed_at":"2026-08-05T16:49:12.845810Z","submitted_at":"2024-05-22T11:32:37Z","title":"HighwayLLM: Decision-Making and Navigation in Highway Driving with RL-Informed Language Model","version":1},"cited_work":{"arxiv_id":"2405.13547","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.13547","snapshot_observed_at":"2026-08-07T15:13:46.012182Z","title":"HighwayLLM: Decision-Making and Navigation in Highway Driving with RL-Informed Language Model","venue":"cs.RO","work_id":"eda128ec-b040-4e37-8c8d-58b70fde8c70","year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:40.692441Z"},"links":{"cited_paper":"/paper/2405.13547","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:5bacc904eca8c124bda1f8d550e0d16ddb59dbdddee01121b020644957f9f070","observation_id":"3b0f2862-310e-474d-b8e6-c4f75ddf3572","resolution":{"observed_at":"2026-08-07T15:13:46.115841Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.07608","last_updated":"2025-03-10T17:59:42Z","snapshot_observed_at":"2026-08-01T16:55:41.453922Z","submitted_at":"2025-03-10T17:59:42Z","title":"AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.07608","snapshot_observed_at":"2026-08-07T15:13:40.813952Z","title":"Alphadrive: Unleashing the power of vlms in autonomous driving via reinforcement learning and reasoning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:40.813952Z"},"links":{"cited_paper":"/paper/2503.07608","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:59733a09c491b526aed4aaf6b8235137a87b535a9a27e9748716488299ebaf54","observation_id":"719611fb-4ff4-4c10-a221-4350bbb118fb","resolution":{"observed_at":"2026-08-07T15:13:40.813952Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:49.816728Z","title":"Optimizing autonomous driving for safety: A human- centric approach with llm-enhanced rlhf","venue":null,"work_id":"4f21d3f7-7b5c-441f-84dc-6ce0bc7de3d5","year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:40.932576Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:35d1a4d7834ad56ed503b94c40eb5cb74a8b3e0c7517781f5ee15c44c731e423","observation_id":"d8c34570-3f2e-4e6e-b1f3-48ecccf7f080","resolution":{"observed_at":"2026-08-07T15:13:49.924665Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15544","last_updated":"2024-12-20T04:08:11Z","snapshot_observed_at":"2026-08-06T17:28:05.501969Z","submitted_at":"2024-12-20T04:08:11Z","title":"VLM-RL: A Unified Vision Language Models and Reinforcement Learning Framework for Safe Autonomous Driving","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15544","snapshot_observed_at":"2026-08-07T15:13:41.080485Z","title":"Vlm-rl: A unified vision language models and reinforcement learning framework for safe autonomous driving","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:41.080485Z"},"links":{"cited_paper":"/paper/2412.15544","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:97ddbe06ea1fd1694a3eb402c7d5d4732e2860d263c8ff97b1f06e02d66e3782","observation_id":"028119a4-8591-4506-b4d8-fd400be7334f","resolution":{"observed_at":"2026-08-07T15:13:41.080485Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.15119","last_updated":"2025-02-21T00:42:40Z","snapshot_observed_at":"2026-08-07T18:00:20.942750Z","submitted_at":"2025-02-21T00:42:40Z","title":"CurricuVLM: Towards Safe Autonomous Driving via Personalized Safety-Critical Curriculum Learning with Vision-Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.15119","snapshot_observed_at":"2026-08-07T15:13:41.227622Z","title":"Curricuvlm: Towards safe autonomous driving via personalized safety-critical curriculum learning with vision-language models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:41.227622Z"},"links":{"cited_paper":"/paper/2502.15119","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:1896bafb87c0bcac6bf30ab4b3ad3b09ec49894ca4efa355dfa0bcfbb6f9ec41","observation_id":"4f77f1af-e24f-4541-94ba-e7b2d231e8be","resolution":{"observed_at":"2026-08-07T15:13:41.227622Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.18511","last_updated":"2024-12-24T15:50:10Z","snapshot_observed_at":"2026-08-05T03:48:57.558948Z","submitted_at":"2024-12-24T15:50:10Z","title":"Large Language Model guided Deep Reinforcement Learning for Decision Making in Autonomous Driving","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.18511","snapshot_observed_at":"2026-08-07T15:13:41.382693Z","title":"Large language model guided deep reinforcement learning for decision making in autonomous driving","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:41.382693Z"},"links":{"cited_paper":"/paper/2412.18511","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:9a3913dc06bbc228a620a3289fc40b0777919c9777d4595444fa21f6ad3940dd","observation_id":"65197cca-5cf8-4ba5-975b-8edfac03eb4c","resolution":{"observed_at":"2026-08-07T15:13:41.382693Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.05057","last_updated":"2025-01-09T08:28:16Z","snapshot_observed_at":"2026-08-06T20:08:07.768288Z","submitted_at":"2025-01-09T08:28:16Z","title":"LearningFlow: Automated Policy Learning Workflow for Urban Driving with Large Language Models","version":1},"cited_work":{"arxiv_id":"2501.05057","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.05057","snapshot_observed_at":"2026-08-07T15:13:45.789156Z","title":"LearningFlow: Automated Policy Learning Workflow for Urban Driving with Large Language Models","venue":"cs.RO","work_id":"abd671f5-6cb2-418b-990c-4f6e3ad542e2","year":2025},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:41.473724Z"},"links":{"cited_paper":"/paper/2501.05057","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:e9f5c0bd1fa1746a0949409760879e18a9699717e4bb121a1a096fb91744ec06","observation_id":"eedf6962-2325-4712-84a7-9fae99fe9538","resolution":{"observed_at":"2026-08-07T15:13:45.844889Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:49.643532Z","title":"Autoreward: Closed-loop reward design with large language models for autonomous driving","venue":null,"work_id":"f197729f-6ec6-4f42-b6df-b20e800b9888","year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:41.537346Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:752062e9c78fe694fbb94155b98036dcf68a561d5341bc11b98d0fce1e325512","observation_id":"c08755b0-b041-4819-8163-c018abebf8ee","resolution":{"observed_at":"2026-08-07T15:13:49.714848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16201","last_updated":"2024-12-17T00:12:45Z","snapshot_observed_at":"2026-07-06T20:11:11.053567Z","submitted_at":"2024-12-17T00:12:45Z","title":"CLIP-RLDrive: Human-Aligned Autonomous Driving via CLIP-Based Reward Shaping in Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.16201","snapshot_observed_at":"2026-08-07T15:13:41.718661Z","title":"Clip-rldrive: Human-aligned autonomous driving via clip-based reward shaping in reinforcement learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:41.718661Z"},"links":{"cited_paper":"/paper/2412.16201","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:96755195a6c0ce8549b49d4820067d02c234211e999085b0dc8b431eb160141c","observation_id":"c6dafbe8-d84c-488d-a6ec-cc2581ec03af","resolution":{"observed_at":"2026-08-07T15:13:41.718661Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:49.521938Z","title":"Lord: Large models based opposite reward design for autonomous driving","venue":null,"work_id":"8a021b96-48df-4603-8604-498612af3366","year":2025},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:41.859641Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:1f3f76f56697215338b02a5732427beff32b96972c16b01b9820e4183462b69e","observation_id":"de4a2223-a3f9-40ad-a2c7-57e517325fb0","resolution":{"observed_at":"2026-08-07T15:13:49.575694Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:49.389201Z","title":"Revolve: Reward evolution with large language models for autonomous driving","venue":null,"work_id":"0a073e55-39ae-4a65-9996-328e46394b7e","year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:42.042418Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:06535aa0c8ccbec68639bebecb439d6e66b3f3650a1baeeaa8a154b6388e349c","observation_id":"25070fe4-6866-4766-89c1-5049edc80bd4","resolution":{"observed_at":"2026-08-07T15:13:49.439504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02707","last_updated":"2025-05-18T11:18:56Z","snapshot_observed_at":"2026-08-04T21:25:41.967552Z","submitted_at":"2024-10-03T17:31:31Z","title":"LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02707","snapshot_observed_at":"2026-08-07T15:13:42.187476Z","title":"Llms know more than they show: On the intrinsic representation of llm hallucinations","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:42.187476Z"},"links":{"cited_paper":"/paper/2410.02707","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:6be7034278152fd091734860bd19464bb175b57d07123d3c5002fe6bcb765263","observation_id":"4c469ab0-84ef-4ea2-a378-04983c3998fa","resolution":{"observed_at":"2026-08-07T15:13:42.187476Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.13684","last_updated":"2024-05-22T14:25:41Z","snapshot_observed_at":"2026-07-06T18:17:59.081203Z","submitted_at":"2024-05-22T14:25:41Z","title":"CrossCheckGPT: Universal Hallucination Ranking for Multimodal Foundation Models","version":1},"cited_work":{"arxiv_id":"2405.13684","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.13684","snapshot_observed_at":"2026-08-07T15:13:45.556338Z","title":"CrossCheckGPT: Universal Hallucination Ranking for Multimodal Foundation Models","venue":"cs.CL","work_id":"dba66017-d320-4053-adb1-05c672c5def9","year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:42.283847Z"},"links":{"cited_paper":"/paper/2405.13684","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:5abfcf890b719247c86c854e17d5655addd1fda6cb37007d3bbb7215eee99959","observation_id":"51089c0c-b0b6-4b7e-88ff-5d6cb44f2434","resolution":{"observed_at":"2026-08-07T15:13:45.640239Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.20550","last_updated":"2025-01-17T01:44:44Z","snapshot_observed_at":"2026-08-05T12:38:08.932341Z","submitted_at":"2024-09-30T17:51:15Z","title":"LLM Hallucinations in Practical Code Generation: Phenomena, Mechanism, and Mitigation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.20550","snapshot_observed_at":"2026-08-07T15:13:42.420652Z","title":"Llm hallucinations in practical code generation: Phenomena, mechanism, and mitigation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:42.420652Z"},"links":{"cited_paper":"/paper/2409.20550","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:c6d02fe8af1122f460d788794ed8d8c3cc56855eddfbde07e8650055f46986e6","observation_id":"04727cb5-68c5-4358-9e31-298b38c9dac5","resolution":{"observed_at":"2026-08-07T15:13:42.420652Z","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":"2026-08-07T15:13:42.543190Z","title":"Exploring and evaluating hallucinations in llm-powered code generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:42.543190Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:96373dcbab46617969fce22d3335864c917472892475957b908753d5b56dfc1f","observation_id":"08e6e69b-2aeb-438e-baf7-85869b80993c","resolution":{"observed_at":"2026-08-07T15:13:42.543190Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:49.242715Z","title":"Llm-check: Investigating detection of hallucinations in large language models","venue":null,"work_id":"4981e477-3db6-4150-aee0-7736da54f5e9","year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:42.589997Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:b306b2f10fab0780f3ba3ba1a933bcf15d226bdbb05a8db573dd4672da857065","observation_id":"61c8658f-51b8-47dc-871c-ec81121c270f","resolution":{"observed_at":"2026-08-07T15:13:49.318571Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.23765","last_updated":"2025-07-17T03:46:15Z","snapshot_observed_at":"2026-08-07T16:26:03.329437Z","submitted_at":"2025-03-31T06:30:35Z","title":"STI-Bench: Are MLLMs Ready for Precise Spatial-Temporal World Understanding?","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.23765","snapshot_observed_at":"2026-08-07T15:13:42.676327Z","title":"Sti-bench: Are mllms ready for precise spatial-temporal world understanding? arXiv preprint arXiv:2503.23765, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:42.676327Z"},"links":{"cited_paper":"/paper/2503.23765","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:0472876a2db285ef74e3ea722281a22301f4f7177e5496092d7ee1939809b801","observation_id":"2347f6aa-ac5a-4b8b-a3da-97312c56f293","resolution":{"observed_at":"2026-08-07T15:13:42.676327Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:49.059672Z","title":"Rladapter: Bridging large language models to reinforcement learning in open worlds","venue":null,"work_id":"8b0ef3cd-ef35-4798-830d-84e94db4b396","year":2023},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:42.860628Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:4ba7dda776d84d06aa99750234020e1430f1ef366fb4b1d1c543f80e9606987d","observation_id":"d8f7bdbf-a887-488d-a79a-3bbfa68c98ea","resolution":{"observed_at":"2026-08-07T15:13:49.135974Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T15:13:42.954660Z","title":"Pre-trained language models for interactive decision-making","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:42.954660Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:5237804504443ff0f67c8d195e1a228d607a3cc2a8dc9f316ea6e2b87c9be8f2","observation_id":"386ce246-dca3-4fd5-a1a8-e2456d0e1088","resolution":{"observed_at":"2026-08-07T15:13:42.954660Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.20587","last_updated":"2024-12-17T15:59:44Z","snapshot_observed_at":"2026-07-06T16:41:15.446251Z","submitted_at":"2023-10-31T16:24:17Z","title":"Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.20587","snapshot_observed_at":"2026-08-07T15:13:43.083091Z","title":"Unleashing the power of pre-trained language models for offline reinforcement learning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:43.083091Z"},"links":{"cited_paper":"/paper/2310.20587","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:79594187828c2183d456e799538525da3c6b4c26a450b7e432973cfea76ea305","observation_id":"6f3765b7-752a-414c-acc6-0bb795585cde","resolution":{"observed_at":"2026-08-07T15:13:43.083091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.18127","last_updated":"2024-02-29T03:41:23Z","snapshot_observed_at":"2026-08-01T17:12:24.406074Z","submitted_at":"2023-10-27T13:19:19Z","title":"Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.18127","snapshot_observed_at":"2026-08-07T15:13:43.182597Z","title":"Ask more, know better: Reinforce-learned prompt questions for decision making with large language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:43.182597Z"},"links":{"cited_paper":"/paper/2310.18127","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:700247098aef79a700fdb1dde87ab0c835c76cbcf19af2f61c8333210f980f01","observation_id":"0b0e9a00-1d26-47d0-8065-0e726e961abf","resolution":{"observed_at":"2026-08-07T15:13:43.182597Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.07927","last_updated":"2024-10-10T13:54:11Z","snapshot_observed_at":"2026-07-31T01:01:46.910108Z","submitted_at":"2024-10-10T13:54:11Z","title":"Efficient Reinforcement Learning with Large Language Model Priors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.07927","snapshot_observed_at":"2026-08-07T15:13:43.329899Z","title":"Efficient reinforcement learning with large language model priors","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:43.329899Z"},"links":{"cited_paper":"/paper/2410.07927","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:6f2cfd7feebfc05fc3f5d8dcd3b0df587c272a757e7e1f7a4bd81b0caf352480","observation_id":"305b7bed-a869-4f01-8ebc-60d8f37803b9","resolution":{"observed_at":"2026-08-07T15:13:43.329899Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:48.834870Z","title":"Grounding large language models in interactive environments with online reinforcement learning","venue":null,"work_id":"58209b88-60f9-48b0-b080-98e368d6c1c5","year":2023},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:43.429434Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:ad6a93166b8869bde9cb75d71d84d684fc4bfc0ad7e139c0ad6f94146c253aea","observation_id":"a44a4276-8fdd-4bfc-b637-45f8fa8ca24e","resolution":{"observed_at":"2026-08-07T15:13:48.956077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:48.561891Z","title":"Fine-tuning large vision-language models as decision-making agents via reinforcement learning","venue":null,"work_id":"06c6ecbb-631a-4173-aa36-34c0dc0ec63e","year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:43.509924Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:f050896060f5afa0ab84b200d3465f4c792e66956f22f32b0674bcf374c52887","observation_id":"f8be9a38-554c-4843-ad3b-a756f3556c6b","resolution":{"observed_at":"2026-08-07T15:13:48.691903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04642","last_updated":"2024-03-07T16:36:29Z","snapshot_observed_at":"2026-08-07T01:30:54.327974Z","submitted_at":"2024-03-07T16:36:29Z","title":"Teaching Large Language Models to Reason with Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04642","snapshot_observed_at":"2026-08-07T15:13:43.610133Z","title":"Teaching large language models to reason with reinforcement learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:43.610133Z"},"links":{"cited_paper":"/paper/2403.04642","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:44096c62062bff15d0c64459da61f8fa19c337eccace400e18fd713d69613483","observation_id":"49fc1608-b320-4489-bbfa-ae4d409b03ac","resolution":{"observed_at":"2026-08-07T15:13:43.610133Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:48.401387Z","title":"Latent reward: Llm-empowered credit assignment in episodic reinforcement learning","venue":null,"work_id":"4bac5c65-678d-49f1-a689-58a027a404d0","year":2025},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:43.722332Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:7aad3f832f9fa2c901f3d432034be1a91421807cca585c14e2484adb78c29ebe","observation_id":"39dd5d8d-80d1-4511-941a-70db42fcaf31","resolution":{"observed_at":"2026-08-07T15:13:48.459332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.11489","last_updated":"2024-05-25T06:42:10Z","snapshot_observed_at":"2026-08-06T20:26:56.795511Z","submitted_at":"2023-09-20T17:39:13Z","title":"Text2Reward: Reward Shaping with Language Models for Reinforcement Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.11489","snapshot_observed_at":"2026-08-07T15:13:43.841984Z","title":"Text2reward: Reward shaping with language models for reinforcement learning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:43.841984Z"},"links":{"cited_paper":"/paper/2309.11489","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:8dacd52c1ed025e3d06ad418192d48b05236c5a6ab6963c65e911080dbc3eaa0","observation_id":"869f221a-4444-4f51-bd69-bb2e6a21cab0","resolution":{"observed_at":"2026-08-07T15:13:43.841984Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.12530","last_updated":"2022-10-22T19:09:18Z","snapshot_observed_at":"2026-07-06T14:09:09.407591Z","submitted_at":"2022-10-22T19:09:18Z","title":"LMPriors: Pre-Trained Language Models as Task-Specific Priors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.12530","snapshot_observed_at":"2026-08-07T15:13:43.958248Z","title":"Lmpriors: Pre-trained language models as task-specific priors","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:43.958248Z"},"links":{"cited_paper":"/paper/2210.12530","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:061aeb938b2087a8db9fd52e64039010dc37b28ca7e0a3594b8c07dea170b047","observation_id":"e940e4c9-cec3-478d-ae1a-6dbb6b0c12ed","resolution":{"observed_at":"2026-08-07T15:13:43.958248Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:47.726264Z","title":"Guiding pretraining in reinforcement learning with large language models","venue":null,"work_id":"2dc5a530-0f67-4605-a81a-7850e795efcd","year":2023},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:44.043046Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:0a231bea3d5bde71e301c47ea38c5f757b6b2da9808c121d44f5a8a0b058ce67","observation_id":"c358db97-b953-4c50-a735-7a8a38bdc92e","resolution":{"observed_at":"2026-08-07T15:13:48.198912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12931","last_updated":"2024-04-30T21:35:53Z","snapshot_observed_at":"2026-08-02T10:40:03.816188Z","submitted_at":"2023-10-19T17:31:01Z","title":"Eureka: Human-Level Reward Design via Coding Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.12931","snapshot_observed_at":"2026-08-07T15:13:44.120140Z","title":"Eureka: Human-level reward design via coding large language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:44.120140Z"},"links":{"cited_paper":"/paper/2310.12931","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:e63e071b1500f72ba9a7dc7d800dd5a2c773c5ba4ee74d23f90ec74f871f6cc7","observation_id":"8ac7e83e-5021-4a5d-8aa8-a77f1b2d40bf","resolution":{"observed_at":"2026-08-07T15:13:44.120140Z","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":"2026-08-07T15:13:44.247133Z","title":"Shufflenet v2: Practical guidelines for efficient cnn architecture design","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:44.247133Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:5ae93dd8cf3e28bb5ddf1c5b52ff17e4e5689853cd29adf3495150b5499c337c","observation_id":"649aa1a4-53e4-4146-b8c7-1144ed8be791","resolution":{"observed_at":"2026-08-07T15:13:44.247133Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-07T15:13:44.372579Z","title":"Proximal policy optimization algorithms","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:44.372579Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:5dfa3f9d9099bbe737af10d8b8e95d674081676ade2d73202cbd45a531ab75cc","observation_id":"4999fcf0-a1ce-451e-a25a-a8d5fd7f9ba5","resolution":{"observed_at":"2026-08-07T15:13:44.372579Z","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":"2026-08-07T15:13:44.417563Z","title":"Retrieval-augmented generation for knowledge- intensive nlp tasks","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:44.417563Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:81d618e598e48b4f1118c09b8f51ff2c5dd4378ea9beeaa551d1905d174c9019","observation_id":"df58aec2-3e55-45fb-8d7e-0f58277e824d","resolution":{"observed_at":"2026-08-07T15:13:44.417563Z","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":"2026-08-07T15:13:44.473392Z","title":"Driving with regulation: Interpretable decision-making for autonomous vehicles with retrieval-augmented reasoning via llm","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:44.473392Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:76a2bcea5f780b46e1ce607cf300e7d78c95e0ef03c1c68a046aae51ffd664b4","observation_id":"df81cc2c-9184-42ad-8da9-b16693c0deb5","resolution":{"observed_at":"2026-08-07T15:13:44.473392Z","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":"2026-08-07T15:13:44.607686Z","title":"Rag-driver: Generalisable driving explanations with retrieval-augmented in-context learning in multi-modal large language model","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:44.607686Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:cb14c886f16393391268889e1f363fafec39e79047348dbbd0f24d2552927923","observation_id":"8107abfc-1589-46f6-a2e0-3326276dc0bf","resolution":{"observed_at":"2026-08-07T15:13:44.607686Z","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":"2026-08-07T15:13:44.726077Z","title":"Billion-scale similarity search with gpus","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:44.726077Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:1e3c431131443415604b52ca9a53cb575674327bdbb8635c5dbd4ed27dd4e9aa","observation_id":"aca40825-2ce7-436a-b106-689c7f1c11e9","resolution":{"observed_at":"2026-08-07T15:13:44.726077Z","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":"2026-08-07T15:13:44.834069Z","title":"Carla: An open urban driving simulator","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:44.834069Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:535b6b6650ac032a4fff328215efdb8c559c56da768eb256b7943bfbb4087071","observation_id":"91c11edf-32d0-4aae-bb79-d51caa1c1e9a","resolution":{"observed_at":"2026-08-07T15:13:44.834069Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:47.531652Z","title":"An end-to-end curriculum learning approach for autonomous driving scenarios","venue":null,"work_id":"8e7813a9-3919-4e1c-b0b4-a62c3f17c6e0","year":2022},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:44.950989Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:3bd7565ea6a18aebb1baa3608316b6a32337a975b85f22bb0f5d02c7dfbae6e0","observation_id":"5b5fd332-5878-418a-bd71-ba438cc30a95","resolution":{"observed_at":"2026-08-07T15:13:47.587803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:13:47.324377Z","title":"Standards for passenger comfort in automated vehicles: Acceleration and jerk","venue":null,"work_id":"953fe234-62ca-42fe-929a-e2d4b92ce117","year":2023},"citing_paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T15:13:45.072007Z"},"links":{"citing_paper":"/paper/2505.15793"},"observation_digest":"sha256:c1fca81f66d4aa4bcdf72ce7f572fe902c48b7db6d57a2d0813c67e28a01bdfe","observation_id":"1b51b106-22e6-48b1-b840-d293a1d5ee2a","resolution":{"observed_at":"2026-08-07T15:13:47.450614Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.15793","last_updated":"2025-05-22T04:48:12Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-07T15:09:16.633906Z","submitted_at":"2025-05-21T17:47:24Z","title":"HCRMP: A LLM-Hinted Contextual Reinforcement Learning Framework for Autonomous Driving"},"reference_resolution":{"displayed":60,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":37,"verified_exact":5,"verified_fuzzy":18},"total_outbound_references":60},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2505.15793."}