{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:F6NAMQ7WX7GCP7QFJIS5ZUXI2I","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"09d8a24829a891163dee9d9b6803a9826d0a3c84d9f388fd8018b4d84ce26e2c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2026-02-26T09:37:38Z","title_canon_sha256":"6f901d0de284f15dc0320803b1f2ae01c6a0458506d4a012a59cb3a0a533064b"},"schema_version":"1.0","source":{"id":"2602.22801","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.22801","created_at":"2026-05-20T00:03:06Z"},{"alias_kind":"arxiv_version","alias_value":"2602.22801v2","created_at":"2026-05-20T00:03:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.22801","created_at":"2026-05-20T00:03:06Z"},{"alias_kind":"pith_short_12","alias_value":"F6NAMQ7WX7GC","created_at":"2026-05-20T00:03:06Z"},{"alias_kind":"pith_short_16","alias_value":"F6NAMQ7WX7GCP7QF","created_at":"2026-05-20T00:03:06Z"},{"alias_kind":"pith_short_8","alias_value":"F6NAMQ7W","created_at":"2026-05-20T00:03:06Z"}],"graph_snapshots":[{"event_id":"sha256:2321ad6b7701d125183b039a3232dfbdd169ce251a2e9bc36b02e7ce388480ff","target":"graph","created_at":"2026-05-20T00:03:06Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2602.22801/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion models have become a popular choice for decision-making tasks in robotics, and more recently, are also being considered for solving autonomous driving tasks. However, their applications and evaluations in autonomous driving remain limited to simulation-based or laboratory settings. The full strength of diffusion models for large-scale, complex real-world settings, such as End-to-End Autonomous Driving (E2E AD), remains underexplored. In this study, we conducted a systematic and large-scale investigation to unleash the potential of the diffusion models as planners for E2E AD, based on","authors_text":"Bin Huang, Enguang Liu, Guang Chen, Hangjun Ye, Jianlin Zhang, Jianwei Cui, Jingjing Liu, Kun Ma, Long Chen, Ruiming Liang, Tianyi Tan, Xianyuan Zhan, Ya-Qin Zhang, Yinan Zheng","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2026-02-26T09:37:38Z","title":"Unleashing the Potential of Diffusion Models for End-to-End Autonomous Driving"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.22801","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:b58b52ffc9bc02eb33c451019ce22ab813f5bb4458fe27add3b3ef0361ca1082","target":"record","created_at":"2026-05-20T00:03:06Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"09d8a24829a891163dee9d9b6803a9826d0a3c84d9f388fd8018b4d84ce26e2c","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2026-02-26T09:37:38Z","title_canon_sha256":"6f901d0de284f15dc0320803b1f2ae01c6a0458506d4a012a59cb3a0a533064b"},"schema_version":"1.0","source":{"id":"2602.22801","kind":"arxiv","version":2}},"canonical_sha256":"2f9a0643f6bfcc27fe054a25dcd2e8d21937132b7981730f63b0fabac28444f0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2f9a0643f6bfcc27fe054a25dcd2e8d21937132b7981730f63b0fabac28444f0","first_computed_at":"2026-05-20T00:03:06.935292Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:03:06.935292Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XX7rt3ZbmE1oFESff1E4K7oS7xCvTvXVyVMayvvdLiGg6WL9+6W4Lm7rjfsizxXSbdhsd2Z8pekcXCxnZ0caCg==","signature_status":"signed_v1","signed_at":"2026-05-20T00:03:06.936270Z","signed_message":"canonical_sha256_bytes"},"source_id":"2602.22801","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b58b52ffc9bc02eb33c451019ce22ab813f5bb4458fe27add3b3ef0361ca1082","sha256:2321ad6b7701d125183b039a3232dfbdd169ce251a2e9bc36b02e7ce388480ff"],"state_sha256":"fb7df86f5676cd1d5f91595316f5925b98baa522227ff29be451b560e1bfada8"}