{"as_of":"2026-08-19T03:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a2925229d5fde80dbb98f50127b0638526ea310cc0d550460c1808a9876958e4","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T22:20:39.075611Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T11:39:46.342700Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2307.07176","last_updated":"2024-08-07T19:08:36Z","snapshot_observed_at":"2026-08-16T15:16:19.883933Z","submitted_at":"2023-07-14T06:00:08Z","title":"SafeDreamer: Safe Reinforcement Learning with World Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.07176","snapshot_observed_at":"2026-08-11T22:20:39.075611Z","title":"SafeDreamer: Safe reinforcement learn- ing with world models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.03568","last_updated":"2024-12-04T18:59:05Z","snapshot_observed_at":"2026-08-17T08:30:58.061060Z","submitted_at":"2024-12-04T18:59:05Z","title":"The Matrix: Infinite-Horizon World Generation with Real-Time Moving Control","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T22:20:39.075611Z"},"links":{"cited_paper":"/paper/2307.07176","citing_paper":"/paper/2412.03568"},"observation_digest":"sha256:04d79d350bb197e4eb2c3aee512d666e852f3c7984c13e8336dab893efa2b525","observation_id":"fe426637-1127-4f95-83d8-22ce86d5bfe4","resolution":{"observed_at":"2026-08-11T22:20:39.075611Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.07176","last_updated":"2024-08-07T19:08:36Z","snapshot_observed_at":"2026-08-16T15:16:19.883933Z","submitted_at":"2023-07-14T06:00:08Z","title":"SafeDreamer: Safe Reinforcement Learning with World Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.07176","snapshot_observed_at":"2026-08-11T21:46:47.751481Z","title":"Safe dreamerv3: Safe reinforcement learning with world models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.04153","last_updated":"2025-04-18T13:37:59Z","snapshot_observed_at":"2026-08-15T10:52:17.229828Z","submitted_at":"2024-12-05T13:32:02Z","title":"A Dynamic Safety Shield for Safe and Efficient Reinforcement Learning of Navigation Tasks","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-11T21:46:47.751481Z"},"links":{"cited_paper":"/paper/2307.07176","citing_paper":"/paper/2412.04153"},"observation_digest":"sha256:433928e98deef97880e6188e8b3de7b1571a8d5fd40199cf30b93db4b75fbf1a","observation_id":"e576be2f-df30-48da-a4f2-c6ef8a46f042","resolution":{"observed_at":"2026-08-11T21:46:47.751481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.07176","last_updated":"2024-08-07T19:08:36Z","snapshot_observed_at":"2026-08-16T15:16:19.883933Z","submitted_at":"2023-07-14T06:00:08Z","title":"SafeDreamer: Safe Reinforcement Learning with World Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.07176","snapshot_observed_at":"2026-08-05T21:02:04.495528Z","title":"Safedreamer: Safe reinforcement learning with world models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.09561","last_updated":"2025-08-13T07:29:40Z","snapshot_observed_at":"2026-08-13T04:24:45.349504Z","submitted_at":"2025-08-13T07:29:40Z","title":"Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges","version":1},"reference_index":110,"source":"pdf_text","source_observed_at":"2026-08-05T21:02:04.495528Z"},"links":{"cited_paper":"/paper/2307.07176","citing_paper":"/paper/2508.09561"},"observation_digest":"sha256:9e002450a879500163bfd49f2fa5c765e20b70a16acce0e762c94bd02a542824","observation_id":"294ead49-44c3-4c34-bcf5-4c6b5ffd7b7a","resolution":{"observed_at":"2026-08-05T21:02:04.495528Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.07176","last_updated":"2024-08-07T19:08:36Z","snapshot_observed_at":"2026-08-16T15:16:19.883933Z","submitted_at":"2023-07-14T06:00:08Z","title":"SafeDreamer: Safe Reinforcement Learning with World Models","version":3},"cited_work":{"arxiv_id":"2307.07176","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.07176","snapshot_observed_at":"2026-07-04T11:39:46.342700Z","title":"Safedreamer: Safe reinforcement learn- ing with world models.arXiv preprint arXiv:2307.07176","venue":null,"work_id":"f398b9f9-4f4a-49bc-bdd0-03c8973d7ed4","year":2024},"citing_paper":{"arxiv_id":"2512.10226","last_updated":"2026-04-14T00:44:42Z","snapshot_observed_at":"2026-08-14T11:48:00.868309Z","submitted_at":"2025-12-11T02:22:07Z","title":"Latent Chain-of-Thought World Modeling for End-to-End Driving","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-16T23:16:41.916869Z"},"links":{"cited_paper":"/paper/2307.07176","citing_paper":"/paper/2512.10226"},"observation_digest":"sha256:fe73f96c69ac9300a84da85bc05039f1b5fd45039b3aa87fa66a51a89a2d2548","observation_id":"047c8e9d-7af6-49b8-9f22-cdf7c3b46b34","resolution":{"observed_at":"2026-05-16T23:18:39.868019Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.07176","last_updated":"2024-08-07T19:08:36Z","snapshot_observed_at":"2026-08-16T15:16:19.883933Z","submitted_at":"2023-07-14T06:00:08Z","title":"SafeDreamer: Safe Reinforcement Learning with World Models","version":3},"cited_work":{"arxiv_id":"2307.07176","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.07176","snapshot_observed_at":"2026-07-04T11:39:46.342700Z","title":"Safedreamer: Safe reinforcement learn- ing with world models.arXiv preprint arXiv:2307.07176","venue":null,"work_id":"f398b9f9-4f4a-49bc-bdd0-03c8973d7ed4","year":2024},"citing_paper":{"arxiv_id":"2604.01346","last_updated":"2026-04-06T19:07:02Z","snapshot_observed_at":"2026-08-14T14:47:33.353946Z","submitted_at":"2026-04-01T19:57:33Z","title":"Safety, Security, and Cognitive Risks in World Models","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-13T22:35:46.126714Z"},"links":{"cited_paper":"/paper/2307.07176","citing_paper":"/paper/2604.01346"},"observation_digest":"sha256:1d3f713b5718b9912a458d988e34143f27daeae5a3a1468d844907ab18476a24","observation_id":"7d629319-7770-4813-847e-9134920ff131","resolution":{"observed_at":"2026-05-13T22:38:22.229588Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.07176","last_updated":"2024-08-07T19:08:36Z","snapshot_observed_at":"2026-08-16T15:16:19.883933Z","submitted_at":"2023-07-14T06:00:08Z","title":"SafeDreamer: Safe Reinforcement Learning with World Models","version":3},"cited_work":{"arxiv_id":"2307.07176","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.07176","snapshot_observed_at":"2026-07-04T11:39:46.342700Z","title":"Safedreamer: Safe reinforcement learn- ing with world models.arXiv preprint arXiv:2307.07176","venue":null,"work_id":"f398b9f9-4f4a-49bc-bdd0-03c8973d7ed4","year":2024},"citing_paper":{"arxiv_id":"2604.16592","last_updated":"2026-04-17T17:51:46Z","snapshot_observed_at":"2026-07-06T23:03:52.631613Z","submitted_at":"2026-04-17T17:51:46Z","title":"Human Cognition in Machines: A Unified Perspective of World Models","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-10T08:12:15.663761Z"},"links":{"cited_paper":"/paper/2307.07176","citing_paper":"/paper/2604.16592"},"observation_digest":"sha256:008e4c5a724043b70f51047e371f03fe454102652f767398758b7d3fbd184c29","observation_id":"415a9774-2dd5-460a-a03b-077bc69673d2","resolution":{"observed_at":"2026-05-10T08:12:26.089047Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.07176","last_updated":"2024-08-07T19:08:36Z","snapshot_observed_at":"2026-08-16T15:16:19.883933Z","submitted_at":"2023-07-14T06:00:08Z","title":"SafeDreamer: Safe Reinforcement Learning with World Models","version":3},"cited_work":{"arxiv_id":"2307.07176","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.07176","snapshot_observed_at":"2026-07-04T11:39:46.342700Z","title":"Safedreamer: Safe reinforcement learn- ing with world models.arXiv preprint arXiv:2307.07176","venue":null,"work_id":"f398b9f9-4f4a-49bc-bdd0-03c8973d7ed4","year":2024},"citing_paper":{"arxiv_id":"2606.10228","last_updated":"2026-06-08T22:40:45Z","snapshot_observed_at":"2026-08-14T07:30:11.091140Z","submitted_at":"2026-06-08T22:40:45Z","title":"SHAPO: Sharpness-Aware Policy Optimization for Safe Exploration","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-27T16:58:19.848530Z"},"links":{"cited_paper":"/paper/2307.07176","citing_paper":"/paper/2606.10228"},"observation_digest":"sha256:7f3119a40400492ef4f032794be6f7e3b51db58aea7289196695bc71ff65fee2","observation_id":"99ead070-5d40-4f7c-9546-9259b3a6d083","resolution":{"observed_at":"2026-07-03T00:57:29.843808Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.07176","last_updated":"2024-08-07T19:08:36Z","snapshot_observed_at":"2026-08-16T15:16:19.883933Z","submitted_at":"2023-07-14T06:00:08Z","title":"SafeDreamer: Safe Reinforcement Learning with World Models","version":3},"cited_work":{"arxiv_id":"2307.07176","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.07176","snapshot_observed_at":"2026-07-04T11:39:46.342700Z","title":"Safedreamer: Safe reinforcement learn- ing with world models.arXiv preprint arXiv:2307.07176","venue":null,"work_id":"f398b9f9-4f4a-49bc-bdd0-03c8973d7ed4","year":2024},"citing_paper":{"arxiv_id":"2606.24010","last_updated":"2026-06-22T23:32:23Z","snapshot_observed_at":"2026-08-13T23:46:59.574745Z","submitted_at":"2026-06-22T23:32:23Z","title":"Safe and Generalizable Hierarchical Multi-Agent RL via Constraint Manifold Control","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-06-26T07:54:12.950136Z"},"links":{"cited_paper":"/paper/2307.07176","citing_paper":"/paper/2606.24010"},"observation_digest":"sha256:5a6cea6ff7f45a10027760d88726e5f66bd1e238d7758ab490b052a89c793ae8","observation_id":"ac1becde-9cad-40ef-a34e-b536ed95c49b","resolution":{"observed_at":"2026-07-04T11:39:46.344610Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2307.07176/citation-record","integrity":"/paper/2307.07176/integrity","json":"/paper/2307.07176/citation-record.json","paper":"/paper/2307.07176"},"outbound":[],"paper":{"arxiv_id":"2307.07176","last_updated":"2024-08-07T19:08:36Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T15:16:19.883933Z","submitted_at":"2023-07-14T06:00:08Z","title":"SafeDreamer: Safe Reinforcement Learning with World Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2307.07176."}