{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:XIFDSCM33KUB23HVXNANXZNZIO","short_pith_number":"pith:XIFDSCM3","canonical_record":{"source":{"id":"2404.12031","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-04-18T09:31:03Z","cross_cats_sorted":[],"title_canon_sha256":"35bfbe07c125be78780538fe68b789087c9750b0275e0fa7dd44dd72dbb57091","abstract_canon_sha256":"deaf18b22f423e47032edcba2c43de0ce81d23c30bcef24a96417e68b5deaac5"},"schema_version":"1.0"},"canonical_sha256":"ba0a39099bdaa81d6cf5bb40dbe5b943a05db30243c964e8c1dc169ada9a4974","source":{"kind":"arxiv","id":"2404.12031","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.12031","created_at":"2026-07-05T08:09:34Z"},{"alias_kind":"arxiv_version","alias_value":"2404.12031v1","created_at":"2026-07-05T08:09:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.12031","created_at":"2026-07-05T08:09:34Z"},{"alias_kind":"pith_short_12","alias_value":"XIFDSCM33KUB","created_at":"2026-07-05T08:09:34Z"},{"alias_kind":"pith_short_16","alias_value":"XIFDSCM33KUB23HV","created_at":"2026-07-05T08:09:34Z"},{"alias_kind":"pith_short_8","alias_value":"XIFDSCM3","created_at":"2026-07-05T08:09:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:XIFDSCM33KUB23HVXNANXZNZIO","target":"record","payload":{"canonical_record":{"source":{"id":"2404.12031","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-04-18T09:31:03Z","cross_cats_sorted":[],"title_canon_sha256":"35bfbe07c125be78780538fe68b789087c9750b0275e0fa7dd44dd72dbb57091","abstract_canon_sha256":"deaf18b22f423e47032edcba2c43de0ce81d23c30bcef24a96417e68b5deaac5"},"schema_version":"1.0"},"canonical_sha256":"ba0a39099bdaa81d6cf5bb40dbe5b943a05db30243c964e8c1dc169ada9a4974","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:09:34.349958Z","signature_b64":"bhgLi0xJJce7qLHs9NybAmKcy4dms+YeTD2dIC3JofKUL+wMEd/g62YBeTcIdN0DFViUDpVk9gNj4GHvKoI1Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ba0a39099bdaa81d6cf5bb40dbe5b943a05db30243c964e8c1dc169ada9a4974","last_reissued_at":"2026-07-05T08:09:34.349449Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:09:34.349449Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.12031","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:09:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sOEgeDEjtdmI8LHvLkXf3TKTv2uga5XCj31ttcIC9d554WrE2pnbnEMic6+qanwzU+V+p0LT6VXU/IJJYOfzAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T23:36:32.322292Z"},"content_sha256":"091a5c10b631e19b8a42c10b21fe323a9e4c81c5d4e62f3941d0b518b56935d6","schema_version":"1.0","event_id":"sha256:091a5c10b631e19b8a42c10b21fe323a9e4c81c5d4e62f3941d0b518b56935d6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:XIFDSCM33KUB23HVXNANXZNZIO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MLS-Track: Multilevel Semantic Interaction in RMOT","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Delong Liu, Fei Su, Jingyu Wang, Song Yang, Zeliang Ma, Zhe Cui, Zhicheng Zhao","submitted_at":"2024-04-18T09:31:03Z","abstract_excerpt":"The new trend in multi-object tracking task is to track objects of interest using natural language. However, the scarcity of paired prompt-instance data hinders its progress. To address this challenge, we propose a high-quality yet low-cost data generation method base on Unreal Engine 5 and construct a brand-new benchmark dataset, named Refer-UE-City, which primarily includes scenes from intersection surveillance videos, detailing the appearance and actions of people and vehicles. Specifically, it provides 14 videos with a total of 714 expressions, and is comparable in scale to the Refer-KITTI"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.12031","kind":"arxiv","version":1},"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/2404.12031/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":"2026-07-05T08:09:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2LGGRTiAYAfjZ0SkOqEkpzsiPosOxmRSj/1BjZ1/RfENESJXFl9HRPBMN2nl95U4bQgXL4mDM0c5SS7uZbWQCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T23:36:32.322837Z"},"content_sha256":"9a8269839a858b261fdaaec8d261db9f0dda36684614ffd9fa2b2af402264060","schema_version":"1.0","event_id":"sha256:9a8269839a858b261fdaaec8d261db9f0dda36684614ffd9fa2b2af402264060"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XIFDSCM33KUB23HVXNANXZNZIO/bundle.json","state_url":"https://pith.science/pith/XIFDSCM33KUB23HVXNANXZNZIO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XIFDSCM33KUB23HVXNANXZNZIO/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":"2026-08-04T23:36:32Z","links":{"resolver":"https://pith.science/pith/XIFDSCM33KUB23HVXNANXZNZIO","bundle":"https://pith.science/pith/XIFDSCM33KUB23HVXNANXZNZIO/bundle.json","state":"https://pith.science/pith/XIFDSCM33KUB23HVXNANXZNZIO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XIFDSCM33KUB23HVXNANXZNZIO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XIFDSCM33KUB23HVXNANXZNZIO","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":"deaf18b22f423e47032edcba2c43de0ce81d23c30bcef24a96417e68b5deaac5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-04-18T09:31:03Z","title_canon_sha256":"35bfbe07c125be78780538fe68b789087c9750b0275e0fa7dd44dd72dbb57091"},"schema_version":"1.0","source":{"id":"2404.12031","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.12031","created_at":"2026-07-05T08:09:34Z"},{"alias_kind":"arxiv_version","alias_value":"2404.12031v1","created_at":"2026-07-05T08:09:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.12031","created_at":"2026-07-05T08:09:34Z"},{"alias_kind":"pith_short_12","alias_value":"XIFDSCM33KUB","created_at":"2026-07-05T08:09:34Z"},{"alias_kind":"pith_short_16","alias_value":"XIFDSCM33KUB23HV","created_at":"2026-07-05T08:09:34Z"},{"alias_kind":"pith_short_8","alias_value":"XIFDSCM3","created_at":"2026-07-05T08:09:34Z"}],"graph_snapshots":[{"event_id":"sha256:9a8269839a858b261fdaaec8d261db9f0dda36684614ffd9fa2b2af402264060","target":"graph","created_at":"2026-07-05T08:09:34Z","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/2404.12031/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The new trend in multi-object tracking task is to track objects of interest using natural language. However, the scarcity of paired prompt-instance data hinders its progress. To address this challenge, we propose a high-quality yet low-cost data generation method base on Unreal Engine 5 and construct a brand-new benchmark dataset, named Refer-UE-City, which primarily includes scenes from intersection surveillance videos, detailing the appearance and actions of people and vehicles. Specifically, it provides 14 videos with a total of 714 expressions, and is comparable in scale to the Refer-KITTI","authors_text":"Delong Liu, Fei Su, Jingyu Wang, Song Yang, Zeliang Ma, Zhe Cui, Zhicheng Zhao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-04-18T09:31:03Z","title":"MLS-Track: Multilevel Semantic Interaction in RMOT"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.12031","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":"sha256:091a5c10b631e19b8a42c10b21fe323a9e4c81c5d4e62f3941d0b518b56935d6","target":"record","created_at":"2026-07-05T08:09:34Z","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":"deaf18b22f423e47032edcba2c43de0ce81d23c30bcef24a96417e68b5deaac5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-04-18T09:31:03Z","title_canon_sha256":"35bfbe07c125be78780538fe68b789087c9750b0275e0fa7dd44dd72dbb57091"},"schema_version":"1.0","source":{"id":"2404.12031","kind":"arxiv","version":1}},"canonical_sha256":"ba0a39099bdaa81d6cf5bb40dbe5b943a05db30243c964e8c1dc169ada9a4974","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ba0a39099bdaa81d6cf5bb40dbe5b943a05db30243c964e8c1dc169ada9a4974","first_computed_at":"2026-07-05T08:09:34.349449Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:09:34.349449Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bhgLi0xJJce7qLHs9NybAmKcy4dms+YeTD2dIC3JofKUL+wMEd/g62YBeTcIdN0DFViUDpVk9gNj4GHvKoI1Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T08:09:34.349958Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.12031","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:091a5c10b631e19b8a42c10b21fe323a9e4c81c5d4e62f3941d0b518b56935d6","sha256:9a8269839a858b261fdaaec8d261db9f0dda36684614ffd9fa2b2af402264060"],"state_sha256":"5dbce4be11deca183ac367c606901d2fc4b8c43e6a5de83c58d389bbae7c703e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eMW2J8PEFiI1qn484SRbiUNQwTNyfmI1obTRhaMJFCKIQ8j2ty5dECfJd8LoGER+cpctZ6trKsjXZujGNLEGBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T23:36:32.327711Z","bundle_sha256":"b8a52c4e729dd531d80f6b9ae9528b90419db3459b2911afe2f714c5edf8ccfc"}}