{"as_of":"2026-08-11T09:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b47711c6dab11df0a1a3f2b69745e8a099813994514605fb813a1a56be19ef68","coverage":[{"denominator":45,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":45,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T19:43:49.807116Z","state":"measured"},{"denominator":45,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":45,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+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/2507.04893/citation-record","integrity":"/paper/2507.04893/integrity","json":"/paper/2507.04893/citation-record.json","paper":"/paper/2507.04893"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:43:56.824269Z","title":"Cost of road accident fatalities to the economy,","venue":null,"work_id":"c09f47ca-b527-4a69-b4a5-9c2dc920a0f6","year":2016},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:45.490301Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:b5b19f1ec6194c0ec96384cf9a3b3bdde3e9ad99ebdd485871568694e4c557a6","observation_id":"eae76665-e008-438c-b2bb-692f6a309379","resolution":{"observed_at":"2026-08-06T19:43:56.890857Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:56.683359Z","title":"Crash injury severity prediction considering data imbalance: A wasserstein generative adversarial network with gradient penalty approach,","venue":null,"work_id":"3454788a-ab7f-4e08-abde-23f62f3403ca","year":2023},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:45.589930Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:41113bb88ceced3ceb4c433caec27b3db83f194e2671bdb8d157761240492054","observation_id":"7e532460-71d7-474e-8050-89468a1dbeec","resolution":{"observed_at":"2026-08-06T19:43:56.747816Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:56.569639Z","title":"BConvLSTM: a deep learning-based technique for severity prediction of a traffic crash,","venue":null,"work_id":"82f72bb5-7453-4b84-a632-83bbc0a89e67","year":2024},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:45.693703Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:219b5a94ab57ea6d1152df00724e471cd2c67d230d4d3442a3674e90a34bea2e","observation_id":"ba798540-a470-465d-969e-251a4cf961ea","resolution":{"observed_at":"2026-08-06T19:43:56.619355Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:56.426689Z","title":"Crash severity analysis: A data- enhanced double layer stacking model using semantic understanding,","venue":null,"work_id":"cf2da219-0c79-42ce-89ba-75dd40d3f96b","year":2024},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:45.830995Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:50a3936a2f78c06d5d43ec87b68454f730852302da6cd0c2f44145f15a26afe6","observation_id":"e4fab482-e069-47ed-889c-3cd93c2bb4a8","resolution":{"observed_at":"2026-08-06T19:43:56.488583Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:56.277107Z","title":"Uncertainty-aware probabilistic graph neural networks for road-level traffic accident prediction,","venue":null,"work_id":"3f7f896b-8235-40f3-8a32-20c596ad2b97","year":2023},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:45.904547Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:b8978746f9d2fb7518a95829308aba9db6dd22078c55a5165077e1685dfa0f84","observation_id":"90b4f4c3-bb76-4a5a-8bb7-848cc14a6708","resolution":{"observed_at":"2026-08-06T19:43:56.363759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:56.111432Z","title":"Analyzing crash severity: Human injury severity prediction method based on transformer model,","venue":null,"work_id":"7d359341-8498-4960-97f6-739e2b36402b","year":2025},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:46.003705Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:324f767533eec6468a85b8d10c2ac67ed562f058f6cecb008c0ff2887d568d2d","observation_id":"7ea70ce6-34e8-40ef-b4f4-9e61926ffc49","resolution":{"observed_at":"2026-08-06T19:43:56.206578Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:55.985518Z","title":"The class imbalance problem in deep learning,","venue":null,"work_id":"f1afda41-a339-432c-b9b0-6cf70f12583d","year":2024},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:46.138377Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:81c4bc51445085b26756a58b2c9e39e0d0390c93a4a7750099d00c1674aab485","observation_id":"983a2c46-4e98-4536-9358-565ec85da8ca","resolution":{"observed_at":"2026-08-06T19:43:56.039030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:55.834326Z","title":"Deep neural networks and tabular data: A survey,","venue":null,"work_id":"90f3b6f1-6f53-4ef6-8dd5-e36d2305058a","year":2024},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:46.214181Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:fc322bf38059addfab626acc02838eb72e9071c0899358eaf9ae6cb23dfe2f1e","observation_id":"9efdf9a2-58bc-45aa-b46b-a27b4ec86e0a","resolution":{"observed_at":"2026-08-06T19:43:55.907650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"7867.2024","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:43:50.318418Z","title":"Traffic accident severity prediction based on interpretable deep learning model,","venue":null,"work_id":"628a4b9e-093d-461f-b44f-606f2e343904","year":2025},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:46.343418Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:644d25b684a521e83a09181786339cd36fbc7189e7d587a3a8e720e20522065a","observation_id":"fc40f549-c565-45c9-80d7-29465a93baa3","resolution":{"observed_at":"2026-08-06T19:43:50.374671Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:55.678844Z","title":"Interpretable traffic accident prediction: Attention spatial–temporal multi-graph traffic stream learning approach,","venue":null,"work_id":"15f9a485-2177-4d3c-a127-28b3a95a3552","year":2024},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:46.456434Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:f0bd30603df3fbbf2e066b223639eafd90f82a7a9013cec96793e15ba29485d3","observation_id":"a5939e3c-f172-476c-a051-88e3d5943ce7","resolution":{"observed_at":"2026-08-06T19:43:55.749658Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:55.507304Z","title":"RFCNN: Traffic accident severity prediction based on decision level fusion of machine and deep learning model,","venue":null,"work_id":"d6f6f21c-58b6-45d6-ad58-741a0ef664f1","year":2021},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:46.551971Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:5de5951d4481be70dca3659b797185841694b18a1e5dcb563e1cdf3093f48c35","observation_id":"a6ba392e-d691-4cab-a227-f3e86d3d0296","resolution":{"observed_at":"2026-08-06T19:43:55.577045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:55.386842Z","title":"Explainable artificial intelligence (xai): Con- cepts, taxonomies, opportunities and challenges toward responsible ai,","venue":null,"work_id":"bcc2c599-20a3-45d1-badd-4cbd596d460d","year":2020},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:46.640740Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:bc8f58be7d2517d8dfb907279cf8c644459497884deee517079a65a9502dc8d0","observation_id":"894c206d-764f-493e-860b-06746f389729","resolution":{"observed_at":"2026-08-06T19:43:55.453064Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:55.151762Z","title":"Chain-of-thought prompting elicits reasoning in large lan- guage models,","venue":null,"work_id":"b6132e71-6cf4-452d-bccf-4b81716e2f7d","year":2022},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:46.763739Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:49879ce3b12a81139e7e0842ccdd39a5327a0a26ca588dcee25682ed9cd0fa00","observation_id":"1a610a4f-123c-4366-b881-ad7fd00cf949","resolution":{"observed_at":"2026-08-06T19:43:55.284030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:54.912849Z","title":"Self-consistency improves chain of thought reasoning in language models,","venue":null,"work_id":"29eadd11-9af7-4d9c-ae4b-f9e64ae44a62","year":2023},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:46.903416Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:0ba6277fb48439c93ac46b5eb10fb72138f3e3f70aa84ddece7ffd9baba065af","observation_id":"2176b65c-184d-4e6d-9755-27f4829dcff4","resolution":{"observed_at":"2026-08-06T19:43:55.007259Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:54.623739Z","title":"Hierarchical rein- forcement learning: A comprehensive survey,","venue":null,"work_id":"052faa14-3fad-4b60-af8f-a9a9c9ccdddc","year":2021},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:47.021588Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:5405cdbded62db873485964180b0c1d5118fde9ac44319ed9362baa28ad2a7c4","observation_id":"f750a895-40e9-477c-81ad-e82b379d807a","resolution":{"observed_at":"2026-08-06T19:43:54.745453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:54.432566Z","title":"Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face,","venue":null,"work_id":"375ea190-d5de-462c-b76c-c330f8c7895e","year":2023},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:47.093581Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:33e63f20e14b6cff59949e63b0e2ad0fb753d9fa88b7bc6046626cb62d45f22a","observation_id":"e66d2bca-f6e1-4aec-87ad-7ee7e6fca3f9","resolution":{"observed_at":"2026-08-06T19:43:54.528422Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:54.198072Z","title":"A survey on llm-based multi-agent systems: workflow, infrastructure, and challenges,","venue":null,"work_id":"fdd17909-1b80-41d7-be70-6e797da02463","year":2024},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:47.181215Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:523725efb445b07317457b81536a79e0570e47fcd525c85820b1af6a8d856000","observation_id":"7fc31611-1643-498d-9c00-6e4d2f5975b0","resolution":{"observed_at":"2026-08-06T19:43:54.307962Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.02026","last_updated":"2025-01-03T02:55:44Z","snapshot_observed_at":"2026-08-11T01:14:46.906783Z","submitted_at":"2025-01-03T02:55:44Z","title":"Recursive Decomposition of Logical Thoughts: Framework for Superior Reasoning and Knowledge Propagation in Large Language Models","version":1},"cited_work":{"arxiv_id":"2501.02026","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.02026","snapshot_observed_at":"2026-08-06T19:43:50.052278Z","title":"Recursive Decomposition of Logical Thoughts: Framework for Superior Reasoning and Knowledge Propagation in Large Language Models","venue":"cs.CL","work_id":"e1839523-57c1-470b-a840-6826761dc960","year":2025},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:47.301126Z"},"links":{"cited_paper":"/paper/2501.02026","citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:f8a319147a646d3121bef7319cf75b78a0d122b4d68da2511ae069b403986baa","observation_id":"d0564868-886f-42a2-a58c-08fe1be55ab3","resolution":{"observed_at":"2026-08-06T19:43:50.141195Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:53.981535Z","title":"Teaching small language models to reason,","venue":null,"work_id":"7f94eb1e-070f-452b-888f-790db2649fc6","year":2023},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:47.386507Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:42d8b619712da71696592643d33bd4c9be0a84683fa28d09e3f202d3a7d7e301","observation_id":"bf2c5258-0694-401c-a879-df56739ccc55","resolution":{"observed_at":"2026-08-06T19:43:54.094056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:53.694839Z","title":"Symbolic chain-of-thought distillation: Small models can also “think","venue":null,"work_id":"333893cf-f87e-476d-b1b7-7c94e2602954","year":2023},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:47.462384Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:7c4b0bff1911566f11f0f897abd34f3c2a1c6181d51c214145107c1e889743c9","observation_id":"6145d682-dc7a-454c-bb0b-e5df2d9fae84","resolution":{"observed_at":"2026-08-06T19:43:53.854926Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:53.437016Z","title":"Distilling mathematical reasoning capabilities into small language models,","venue":null,"work_id":"22d32c2d-cea8-4f12-993c-aa1e0d3d69d0","year":2024},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:47.566206Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:35dbd92836ed371cac5a914a7ca8fb0ef1c2a78b12e3119d76328cdffa121226","observation_id":"6e3e78a3-6ac1-44b9-b96d-0131b16ec1cf","resolution":{"observed_at":"2026-08-06T19:43:53.576329Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:53.168111Z","title":"Benchmarking multi-agent deep reinforcement learning algorithms in cooperative tasks,","venue":null,"work_id":"9fff11c7-3c7b-48d6-b9ff-e6b658cc04be","year":2021},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:47.628696Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:3c1507cf29b84307ba04a16fb0a471a10985b9ec49f52a74984ead2e8c0d50a7","observation_id":"338872ee-3707-44db-8919-1ec0a37b29b2","resolution":{"observed_at":"2026-08-06T19:43:53.291064Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:52.947067Z","title":"A survey on multi-agent reinforcement learning and its application,","venue":null,"work_id":"d7d3ef22-c16b-40b7-a3f4-029737673cbe","year":2024},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:47.673388Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:783abb2d011575d52c0e750cac0d37bae78763c8bdf869db90a143f3b901e004","observation_id":"0b066d9b-c402-4a7e-8179-31ca5f2e7d55","resolution":{"observed_at":"2026-08-06T19:43:53.056807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:52.681317Z","title":"Least-to-most prompting enables complex reasoning in large language models,","venue":null,"work_id":"4333bc2e-ef67-4056-8475-c63093581aa6","year":2023},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:47.752596Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:50ca5518c4729e29e9dfe69f29ef7148333d0e808ad621b294dbb4e8307e2be0","observation_id":"7b88795d-ab84-4e16-922c-30376123038f","resolution":{"observed_at":"2026-08-06T19:43:52.822172Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.11916","last_updated":"2023-01-29T05:14:17Z","snapshot_observed_at":"2026-08-07T04:02:08.445660Z","submitted_at":"2022-05-24T09:22:26Z","title":"Large Language Models are Zero-Shot Reasoners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.11916","snapshot_observed_at":"2026-08-06T19:43:47.836236Z","title":"Large language models are zero-shot reasoners,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:47.836236Z"},"links":{"cited_paper":"/paper/2205.11916","citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:e71933de8d0cce67528a40574b6a1208b915d84a82198ded7fd7a68fe90e3ed0","observation_id":"d0e5d446-d8d4-4c05-ac26-b69d34898afa","resolution":{"observed_at":"2026-08-06T19:43:47.836236Z","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":"2026-08-06T19:43:52.457658Z","title":"Generative agents: Interactive simulacra of human be- havior,","venue":null,"work_id":"f95541b0-96e3-40d9-b9aa-a1e87f56bb54","year":2023},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:47.886332Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:64df7b5d823db897aa175eb203d2b0a104644a5c59873cbcea786c3faba53eea","observation_id":"dc6b8380-9cd9-4931-b937-7365add1ffb3","resolution":{"observed_at":"2026-08-06T19:43:52.552733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.11171","last_updated":"2023-03-07T17:57:37Z","snapshot_observed_at":"2026-07-06T12:50:22.773056Z","submitted_at":"2022-03-21T17:48:52Z","title":"Self-Consistency Improves Chain of Thought Reasoning in Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.11171","snapshot_observed_at":"2026-08-06T19:43:48.013009Z","title":"Self-consistency improves chain of thought reasoning in language models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:48.013009Z"},"links":{"cited_paper":"/paper/2203.11171","citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:b1da8eed1267cd4f4da47164a57b5197ad8cc1841058997c0594370e885dff36","observation_id":"d5ae38a4-3697-413d-9062-041523961dab","resolution":{"observed_at":"2026-08-06T19:43:48.013009Z","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":"2026-08-06T19:43:52.226592Z","title":"Least-to- most prompting enables complex reasoning in large language models,","venue":null,"work_id":"1f97a8ce-5aba-4ed4-8a8e-72608365fb0c","year":null},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:48.095987Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:8acf06e72bc4622f8b0db0dc3b8c8c67852767b7a27fd9da46147c7248952215","observation_id":"2e79dffe-74eb-44fd-bf49-5554e3b5a61c","resolution":{"observed_at":"2026-08-06T19:43:52.358928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.09687","last_updated":"2024-02-06T18:00:18Z","snapshot_observed_at":"2026-08-06T03:16:16.175894Z","submitted_at":"2023-08-18T17:29:23Z","title":"Graph of Thoughts: Solving Elaborate Problems with Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.09687","snapshot_observed_at":"2026-08-06T19:43:48.242812Z","title":"Graph of thoughts: Solving elaborate problems with large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:48.242812Z"},"links":{"cited_paper":"/paper/2308.09687","citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:1acbc35aac89ffb9a15e524d45552ba05f473182f3cae56fe194aa00193065aa","observation_id":"d890be8c-0ce0-4046-ab17-4e2787b952de","resolution":{"observed_at":"2026-08-06T19:43:48.242812Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10601","last_updated":"2023-12-03T22:50:35Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-17T23:16:17Z","title":"Tree of Thoughts: Deliberate Problem Solving with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.10601","snapshot_observed_at":"2026-08-06T19:43:48.300457Z","title":"Tree of thoughts: Deliberate problem solving with large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:48.300457Z"},"links":{"cited_paper":"/paper/2305.10601","citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:2a4698d2b6ee70e1ff284ed4adf463ddf7511040e1a6d726a03705ba231ac5ea","observation_id":"b325720f-71da-45c9-9102-8ab1619ca3eb","resolution":{"observed_at":"2026-08-06T19:43:48.300457Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.18600","last_updated":"2025-03-03T17:08:21Z","snapshot_observed_at":"2026-08-07T17:49:06.764625Z","submitted_at":"2025-02-25T19:36:06Z","title":"Chain of Draft: Thinking Faster by Writing Less","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.18600","snapshot_observed_at":"2026-08-06T19:43:48.381491Z","title":"Chain of draft: Thinking faster by writing less,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:48.381491Z"},"links":{"cited_paper":"/paper/2502.18600","citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:795b5758e694b6798c0ba532890e47f8c41c12b6cc988da89dcde875e557bcfd","observation_id":"91130369-6c84-4c90-9799-7328477315e6","resolution":{"observed_at":"2026-08-06T19:43:48.381491Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15594","last_updated":"2025-10-19T10:32:43Z","snapshot_observed_at":"2026-08-02T10:23:50.881300Z","submitted_at":"2024-11-23T16:03:35Z","title":"A Survey on LLM-as-a-Judge","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.15594","snapshot_observed_at":"2026-08-06T19:43:48.464478Z","title":"A survey on llm-as-a-judge,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:48.464478Z"},"links":{"cited_paper":"/paper/2411.15594","citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:bd3d16bcab63e711789c5cf0aadd7b81d00cbabed894d9db7d02eae1304fc12d","observation_id":"962c8aec-b98b-456b-86c4-d29dbf5e949e","resolution":{"observed_at":"2026-08-06T19:43:48.464478Z","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":"2026-08-06T19:43:51.945588Z","title":"A literature review of machine learning algorithms for crash injury severity prediction,","venue":null,"work_id":"3b4f9915-615c-48f1-ad87-bfd71adf7464","year":2022},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:48.550607Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:dd8402cb767bce1934de4ab7f70c563bd2e92637ef687ce07355f6f40ed50dae","observation_id":"be8eeb82-7e47-4a33-85a3-8f9ceb83d555","resolution":{"observed_at":"2026-08-06T19:43:52.101135Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:51.707758Z","title":"Predicting multiple types of traffic accident severity with explanations: A multi-task deep learning frame- work,","venue":null,"work_id":"9e010fa5-0074-4059-a78f-957071e1b245","year":2022},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:48.711874Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:e76d22106282d117763dab78fe103271726d5f2ab96f2af6e5767eff5b12e351","observation_id":"65350d57-cfd0-441d-9412-b4aca666cd65","resolution":{"observed_at":"2026-08-06T19:43:51.824480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:51.427120Z","title":"Comparison of traffic accident injury severity prediction models with explainable machine learning,","venue":null,"work_id":"8c90fb44-3b34-45cb-9eb0-506e82b4c3c8","year":2023},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:48.821825Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:3c7bba81555882a0c4715ae9360cd7a36ca137db8a9fa00c2796f30ac6049969","observation_id":"9795068c-a95f-4260-b54a-4ac88b23f1ac","resolution":{"observed_at":"2026-08-06T19:43:51.565958Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:51.198785Z","title":"RFCNN: Traffic accident severity prediction based on decision level fusion of machine and deep learning model,","venue":null,"work_id":"cad96b43-d787-4ed4-b588-278d31a7707f","year":2021},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:48.884755Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:58e77fba083c7e11b2ec0f3643260ef401cf683a0ff3edff004cfe7afec2efb5","observation_id":"df404e84-8805-4405-bbc0-4f22762335aa","resolution":{"observed_at":"2026-08-06T19:43:51.307001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:50.978982Z","title":"Deep neural networks and tabular data: A survey,","venue":null,"work_id":"23587bf2-ad22-4001-b08b-fd2960bb8696","year":2023},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:48.975016Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:29894ac82a67a05f2b05286bb7c6c5eb9173c4132c500f575c85897b264fc766","observation_id":"1049968b-8bdb-4d71-8b79-b13d102e3339","resolution":{"observed_at":"2026-08-06T19:43:51.103577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.03253","last_updated":"2021-11-23T15:22:04Z","snapshot_observed_at":"2026-07-06T11:16:30.999377Z","submitted_at":"2021-06-06T21:22:39Z","title":"Tabular Data: Deep Learning is Not All You Need","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.03253","snapshot_observed_at":"2026-08-06T19:43:49.080953Z","title":"Tabular data: Deep learning is not all you need,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:49.080953Z"},"links":{"cited_paper":"/paper/2106.03253","citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:1c4f06300782fbaf7321c45b9a23197ef169bda819689e629720d89fd0ebc958","observation_id":"b9342740-0a1d-43f7-925b-4cf79615f84c","resolution":{"observed_at":"2026-08-06T19:43:49.080953Z","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":"2026-08-06T19:43:50.717530Z","title":"A survey on LLM- based multi-agent systems: workflow, infrastructure, and challenges,","venue":null,"work_id":"1d5d9c36-f301-4887-8c07-d4587ea5c09a","year":2024},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:49.225078Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:10e0aa16fa8cf4a8653f4203d3cada0a7a6d65ec0cb76c9142ddd80753d2d87d","observation_id":"58c6dba7-699f-4340-a576-ed2557d38243","resolution":{"observed_at":"2026-08-06T19:43:50.826748Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-06T19:43:49.364096Z","title":"Pre- train, prompt, and predict: A systematic survey of prompting methods in natural language processing,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:49.364096Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:6816ed0345d54c8da92121b2a5052dc381d0c43ca77f4b9392485cccd8679760","observation_id":"15819a96-61de-4111-b37c-41c0e7a38ba0","resolution":{"observed_at":"2026-08-06T19:43:49.364096Z","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":"2026-08-06T19:43:49.462141Z","title":"Language models are few-shot learners,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:49.462141Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:4ad2afed5da1346b931c22e5f46f49863a2ec63b7cc8b1873922d1c54cfc4b8e","observation_id":"bacc8dc5-64bf-4af5-b125-ef86484b47e7","resolution":{"observed_at":"2026-08-06T19:43:49.462141Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2201.11903","last_updated":"2023-01-10T23:07:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-01-28T02:33:07Z","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.11903","snapshot_observed_at":"2026-08-06T19:43:49.596732Z","title":"Chain-of-thought prompting elicits reasoning in large language mod- els,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:49.596732Z"},"links":{"cited_paper":"/paper/2201.11903","citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:a662433b16d108aec589034dae64ec663f60a6bfbfe12556cba39ae201bd9234","observation_id":"6a562a6c-d9aa-4b2d-a0c5-5c1d15a64369","resolution":{"observed_at":"2026-08-06T19:43:49.596732Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.05409","last_updated":"2019-06-12T22:26:06Z","snapshot_observed_at":"2026-08-08T08:39:31.029412Z","submitted_at":"2019-06-12T22:26:06Z","title":"A Countrywide Traffic Accident Dataset","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.05409","snapshot_observed_at":"2026-08-06T19:43:49.718924Z","title":"A countrywide traffic accident dataset,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:49.718924Z"},"links":{"cited_paper":"/paper/1906.05409","citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:507ad45ce2005f59fc645d8a9c376c60071a12b658c3ad632d20f4a1cd1a99e8","observation_id":"88e1fb03-c616-4b6d-b54a-a9670653dcf1","resolution":{"observed_at":"2026-08-06T19:43:49.718924Z","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":"2026-08-06T19:43:50.455430Z","title":"UK Road Safety: Traffic Accidents and Vehicles,","venue":null,"work_id":"9cc2f4b7-c70a-4e14-92ef-ddcc04e16a7e","year":2019},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:49.807116Z"},"links":{"citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:cbc84df95ee36f00ac61e24ec43c6d3714ee1711f8b576ed49a8c1a977b61473","observation_id":"2ca6d8e4-701c-4ec1-9291-3a6b2e5c7052","resolution":{"observed_at":"2026-08-06T19:43:50.544349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.10625","last_updated":"2023-04-16T22:08:08Z","snapshot_observed_at":"2026-08-06T09:00:42.886249Z","submitted_at":"2022-05-21T15:34:53Z","title":"Least-to-Most Prompting Enables Complex Reasoning in Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.10625","snapshot_observed_at":"2026-08-06T19:43:48.159611Z","title":"Available: http://arxiv.org/abs/2205.10625","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:48.159611Z"},"links":{"cited_paper":"/paper/2205.10625","citing_paper":"/paper/2507.04893"},"observation_digest":"sha256:78d2b8fa12a386fb0071bfeec25df43cc143c2ab490cc3da6d15977346b6e311","observation_id":"3224e74a-3725-42b2-be60-2b690dea3ad4","resolution":{"observed_at":"2026-08-06T19:43:48.159611Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.04893","last_updated":"2025-07-07T11:27:49Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-08T08:39:52.710455Z","submitted_at":"2025-07-07T11:27:49Z","title":"MARBLE: A Multi-Agent Rule-Based LLM Reasoning Engine for Accident Severity Prediction"},"reference_resolution":{"displayed":45,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":2,"verified_fuzzy":31},"total_outbound_references":45},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2507.04893."}