{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:23G7G2E3RRXD5WVXTNNI7ODSBV","short_pith_number":"pith:23G7G2E3","canonical_record":{"source":{"id":"2511.21256","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-11-26T10:39:16Z","cross_cats_sorted":[],"title_canon_sha256":"0312696cd28f3b4b575b8bcbf46a2616b22d6946f1792858d2bcd5522a455654","abstract_canon_sha256":"32d781d9abe58dc21cd7ee345b94a1ec67833a8e45d88af94a551827d301949c"},"schema_version":"1.0"},"canonical_sha256":"d6cdf3689b8c6e3edab79b5a8fb8720d40ef6229cb0a89177ad4c7490acf384e","source":{"kind":"arxiv","id":"2511.21256","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2511.21256","created_at":"2026-06-30T01:16:26Z"},{"alias_kind":"arxiv_version","alias_value":"2511.21256v2","created_at":"2026-06-30T01:16:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.21256","created_at":"2026-06-30T01:16:26Z"},{"alias_kind":"pith_short_12","alias_value":"23G7G2E3RRXD","created_at":"2026-06-30T01:16:26Z"},{"alias_kind":"pith_short_16","alias_value":"23G7G2E3RRXD5WVX","created_at":"2026-06-30T01:16:26Z"},{"alias_kind":"pith_short_8","alias_value":"23G7G2E3","created_at":"2026-06-30T01:16:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:23G7G2E3RRXD5WVXTNNI7ODSBV","target":"record","payload":{"canonical_record":{"source":{"id":"2511.21256","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-11-26T10:39:16Z","cross_cats_sorted":[],"title_canon_sha256":"0312696cd28f3b4b575b8bcbf46a2616b22d6946f1792858d2bcd5522a455654","abstract_canon_sha256":"32d781d9abe58dc21cd7ee345b94a1ec67833a8e45d88af94a551827d301949c"},"schema_version":"1.0"},"canonical_sha256":"d6cdf3689b8c6e3edab79b5a8fb8720d40ef6229cb0a89177ad4c7490acf384e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-30T01:16:26.453321Z","signature_b64":"mceKHDNcInkNjAogcfPgfHwAFQNI8cdsSX03+4Fh72nWmfMCU3SWeHV0Ic1fOHE9wkMhYaezlSudsA4tY5M0DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d6cdf3689b8c6e3edab79b5a8fb8720d40ef6229cb0a89177ad4c7490acf384e","last_reissued_at":"2026-06-30T01:16:26.452724Z","signature_status":"signed_v1","first_computed_at":"2026-06-30T01:16:26.452724Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2511.21256","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-30T01:16:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TCBlyPwKKaGOxCTZWVa7zY8SOWiSasBsnLmE6JBSLi4CRz0W9bESD8Rx9eX2EF83Gc8Fecz/YTKlOsty/IyYCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T16:48:52.874260Z"},"content_sha256":"618e0075d2c5de652e7d9511defac97a0e6be6b26e1d6b67578b5dc60e20452b","schema_version":"1.0","event_id":"sha256:618e0075d2c5de652e7d9511defac97a0e6be6b26e1d6b67578b5dc60e20452b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:23G7G2E3RRXD5WVXTNNI7ODSBV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LaGen: Towards Autoregressive LiDAR Scene Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Fanrui Zhang, Jianwen Sun, Junchi Yan, Junjie Li, Junqi You, Juyong Zhang, Sizhuo Zhou, Songbur Wong, Xiaosong Jia, Yukang Feng","submitted_at":"2025-11-26T10:39:16Z","abstract_excerpt":"Generative world models for autonomous driving (AD) are of great value in applications such as data augmentation, closed-loop simulation, and safety-critical scenario evaluation. Unlike the widely studied image modality, in this work we explore generative world models for LiDAR data. Existing generation methods for LiDAR predominantly focus on single frame generation or lack the capacity for interactive simulation, while existing prediction approaches require multiple frames of historical input and can only deterministically predict multiple frames at once. Both paradigms fail to support long-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.21256","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2511.21256/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-30T01:16:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Lu4yALyKgusQLVaqTkzyo7alpmmu+8GxeqyqOC8DJ15htBJh4OY44AmBqwq0HTV3vW2wmRvjgrJquONpWW8SBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T16:48:52.875634Z"},"content_sha256":"5bd9f770f4e0a76f3a5da6939587d3d31c8f4ae941c165b1873a1a3bfd5354a2","schema_version":"1.0","event_id":"sha256:5bd9f770f4e0a76f3a5da6939587d3d31c8f4ae941c165b1873a1a3bfd5354a2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/23G7G2E3RRXD5WVXTNNI7ODSBV/bundle.json","state_url":"https://pith.science/pith/23G7G2E3RRXD5WVXTNNI7ODSBV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/23G7G2E3RRXD5WVXTNNI7ODSBV/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-19T16:48:52Z","links":{"resolver":"https://pith.science/pith/23G7G2E3RRXD5WVXTNNI7ODSBV","bundle":"https://pith.science/pith/23G7G2E3RRXD5WVXTNNI7ODSBV/bundle.json","state":"https://pith.science/pith/23G7G2E3RRXD5WVXTNNI7ODSBV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/23G7G2E3RRXD5WVXTNNI7ODSBV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:23G7G2E3RRXD5WVXTNNI7ODSBV","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":"32d781d9abe58dc21cd7ee345b94a1ec67833a8e45d88af94a551827d301949c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-11-26T10:39:16Z","title_canon_sha256":"0312696cd28f3b4b575b8bcbf46a2616b22d6946f1792858d2bcd5522a455654"},"schema_version":"1.0","source":{"id":"2511.21256","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2511.21256","created_at":"2026-06-30T01:16:26Z"},{"alias_kind":"arxiv_version","alias_value":"2511.21256v2","created_at":"2026-06-30T01:16:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.21256","created_at":"2026-06-30T01:16:26Z"},{"alias_kind":"pith_short_12","alias_value":"23G7G2E3RRXD","created_at":"2026-06-30T01:16:26Z"},{"alias_kind":"pith_short_16","alias_value":"23G7G2E3RRXD5WVX","created_at":"2026-06-30T01:16:26Z"},{"alias_kind":"pith_short_8","alias_value":"23G7G2E3","created_at":"2026-06-30T01:16:26Z"}],"graph_snapshots":[{"event_id":"sha256:5bd9f770f4e0a76f3a5da6939587d3d31c8f4ae941c165b1873a1a3bfd5354a2","target":"graph","created_at":"2026-06-30T01:16:26Z","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/2511.21256/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generative world models for autonomous driving (AD) are of great value in applications such as data augmentation, closed-loop simulation, and safety-critical scenario evaluation. Unlike the widely studied image modality, in this work we explore generative world models for LiDAR data. Existing generation methods for LiDAR predominantly focus on single frame generation or lack the capacity for interactive simulation, while existing prediction approaches require multiple frames of historical input and can only deterministically predict multiple frames at once. Both paradigms fail to support long-","authors_text":"Fanrui Zhang, Jianwen Sun, Junchi Yan, Junjie Li, Junqi You, Juyong Zhang, Sizhuo Zhou, Songbur Wong, Xiaosong Jia, Yukang Feng","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-11-26T10:39:16Z","title":"LaGen: Towards Autoregressive LiDAR Scene Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.21256","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":"sha256:618e0075d2c5de652e7d9511defac97a0e6be6b26e1d6b67578b5dc60e20452b","target":"record","created_at":"2026-06-30T01:16:26Z","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":"32d781d9abe58dc21cd7ee345b94a1ec67833a8e45d88af94a551827d301949c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-11-26T10:39:16Z","title_canon_sha256":"0312696cd28f3b4b575b8bcbf46a2616b22d6946f1792858d2bcd5522a455654"},"schema_version":"1.0","source":{"id":"2511.21256","kind":"arxiv","version":2}},"canonical_sha256":"d6cdf3689b8c6e3edab79b5a8fb8720d40ef6229cb0a89177ad4c7490acf384e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d6cdf3689b8c6e3edab79b5a8fb8720d40ef6229cb0a89177ad4c7490acf384e","first_computed_at":"2026-06-30T01:16:26.452724Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-30T01:16:26.452724Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mceKHDNcInkNjAogcfPgfHwAFQNI8cdsSX03+4Fh72nWmfMCU3SWeHV0Ic1fOHE9wkMhYaezlSudsA4tY5M0DQ==","signature_status":"signed_v1","signed_at":"2026-06-30T01:16:26.453321Z","signed_message":"canonical_sha256_bytes"},"source_id":"2511.21256","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:618e0075d2c5de652e7d9511defac97a0e6be6b26e1d6b67578b5dc60e20452b","sha256:5bd9f770f4e0a76f3a5da6939587d3d31c8f4ae941c165b1873a1a3bfd5354a2"],"state_sha256":"b33458e25a8ad5a0f4d82f7d137cda4d3941e022de32d856c33c23e9e8ca85a2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z4UQISb9X4LkV7eCudYM+L2DOtWDIJgBj5MgV7vVvGOSNizg2NZt5eB5PH6ZxWqu2hajyBBXcAZ/H5QulDtHBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T16:48:52.882945Z","bundle_sha256":"6485e7a2f6ba0424173c3ce16273067a3671ac80b6f7f6561600b48fd23f74fd"}}