{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:BON4ZI2EQMMGFHWHZFZO4BMWKY","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":"723cba6ef06b6bf14d791b022f31671023e8f21e9eafe73a377cc504a973aa89","cross_cats_sorted":["cs.DB"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-25T07:55:49Z","title_canon_sha256":"255bcace6c339fc4388ea68fa4ab7f1ca96e71683af3c14acbb6527ea66422b0"},"schema_version":"1.0","source":{"id":"2605.25538","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.25538","created_at":"2026-05-26T02:04:41Z"},{"alias_kind":"arxiv_version","alias_value":"2605.25538v1","created_at":"2026-05-26T02:04:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.25538","created_at":"2026-05-26T02:04:41Z"},{"alias_kind":"pith_short_12","alias_value":"BON4ZI2EQMMG","created_at":"2026-05-26T02:04:41Z"},{"alias_kind":"pith_short_16","alias_value":"BON4ZI2EQMMGFHWH","created_at":"2026-05-26T02:04:41Z"},{"alias_kind":"pith_short_8","alias_value":"BON4ZI2E","created_at":"2026-05-26T02:04:41Z"}],"graph_snapshots":[{"event_id":"sha256:e16433913dbc930561f12502eaae64f9ad5b73b2653663462f77ccda8c9b2de2","target":"graph","created_at":"2026-05-26T02:04:41Z","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/2605.25538/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Track materialization converts raw video into reusable object tracks that downstream queries can run against without rerunning tracking, but extracting those tracks efficiently and with high fidelity remains expensive. Prior systems reduce cost through temporal frame sampling, erasing the inter-frame motion that fine-grained tracking requires. In stationary video, however, large portions of each frame contain no objects of interest, and the remaining regions tolerate different sampling rates. We present Tetris, a track-extraction system that decomposes videos into a tile-based polyomino data m","authors_text":"Alena Chao, Alvin Cheung, Chanwut Kittivorawong, Charlie Si","cross_cats":["cs.DB"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-25T07:55:49Z","title":"Tetris: Tile-level Sampling for Efficient and High-Fidelity Video Object Tracking"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.25538","kind":"arxiv","version":1},"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":"sha256:59c35c567c4f639323edafba1cba65df0a11e95c349171a750a9759f54112bf2","target":"record","created_at":"2026-05-26T02:04:41Z","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":"723cba6ef06b6bf14d791b022f31671023e8f21e9eafe73a377cc504a973aa89","cross_cats_sorted":["cs.DB"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-25T07:55:49Z","title_canon_sha256":"255bcace6c339fc4388ea68fa4ab7f1ca96e71683af3c14acbb6527ea66422b0"},"schema_version":"1.0","source":{"id":"2605.25538","kind":"arxiv","version":1}},"canonical_sha256":"0b9bcca3448318629ec7c972ee05965635a8cd7a711855bd3fe1679bfd6dbe59","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0b9bcca3448318629ec7c972ee05965635a8cd7a711855bd3fe1679bfd6dbe59","first_computed_at":"2026-05-26T02:04:41.784416Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T02:04:41.784416Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2Zk2L5MP6iGhMAcSXDmKDoewGGss32nGakfP2DUBnbnYNw6vvQq9qNnYzsqJQHmnuEibfAWyoKdLavrEQElWAQ==","signature_status":"signed_v1","signed_at":"2026-05-26T02:04:41.785123Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.25538","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:59c35c567c4f639323edafba1cba65df0a11e95c349171a750a9759f54112bf2","sha256:e16433913dbc930561f12502eaae64f9ad5b73b2653663462f77ccda8c9b2de2"],"state_sha256":"976e962457fcdc63b32b5f978da9b2645f0686d4100f6fd0f3e19d57a3f7a32f"}