{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:UKB4R2LXHKYAQ3P3LSEBVF54YE","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":"a404efbdee490af0919c166ad50fce2dc32917bc13510a8f2df23b9fcd886083","cross_cats_sorted":["cs.AI","cs.IR","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-23T12:58:20Z","title_canon_sha256":"e7914973cbfcc15617194384aa58455e1a6ed6d9e2a71c03f56f48f9f924bb1d"},"schema_version":"1.0","source":{"id":"2209.11572","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.11572","created_at":"2026-05-26T02:04:57Z"},{"alias_kind":"arxiv_version","alias_value":"2209.11572v3","created_at":"2026-05-26T02:04:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.11572","created_at":"2026-05-26T02:04:57Z"},{"alias_kind":"pith_short_12","alias_value":"UKB4R2LXHKYA","created_at":"2026-05-26T02:04:57Z"},{"alias_kind":"pith_short_16","alias_value":"UKB4R2LXHKYAQ3P3","created_at":"2026-05-26T02:04:57Z"},{"alias_kind":"pith_short_8","alias_value":"UKB4R2LX","created_at":"2026-05-26T02:04:57Z"}],"graph_snapshots":[{"event_id":"sha256:f9925ef99bd80a4d63240df948eafa85408e74d3d1ca3a3641a2c8d3677a1f76","target":"graph","created_at":"2026-05-26T02:04:57Z","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/2209.11572/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As an increasingly popular task in multimedia information retrieval, video moment retrieval (VMR) aims to localize the target moment from an untrimmed video according to a given language query. Most previous methods depend heavily on numerous manual annotations (i.e., moment boundaries), which are extremely expensive to acquire in practice. In addition, due to the domain gap between different datasets, directly applying these pre-trained models to an unseen domain leads to a significant performance drop. In this paper, we focus on a novel task: cross-domain VMR, where fully-annotated datasets ","authors_text":"Daizong Liu, Pan Zhou, Xiang Fang, Yuchong Hu","cross_cats":["cs.AI","cs.IR","cs.MM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-23T12:58:20Z","title":"Multi-Modal Cross-Domain Alignment Network for Video Moment Retrieval"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.11572","kind":"arxiv","version":3},"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:b83416f3ed31c5ba1c662cfc32111bdaa359e6c455e01a04109ab07ba99f85ac","target":"record","created_at":"2026-05-26T02:04:57Z","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":"a404efbdee490af0919c166ad50fce2dc32917bc13510a8f2df23b9fcd886083","cross_cats_sorted":["cs.AI","cs.IR","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-09-23T12:58:20Z","title_canon_sha256":"e7914973cbfcc15617194384aa58455e1a6ed6d9e2a71c03f56f48f9f924bb1d"},"schema_version":"1.0","source":{"id":"2209.11572","kind":"arxiv","version":3}},"canonical_sha256":"a283c8e9773ab0086dfb5c881a97bcc1300e70998078371ab85d0205129500bd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a283c8e9773ab0086dfb5c881a97bcc1300e70998078371ab85d0205129500bd","first_computed_at":"2026-05-26T02:04:57.991815Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T02:04:57.991815Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sPNBI2ILEcfrKcADFQ8rUiwgVrWUs3jyLo4LIWSPPZ9IxaEyj6kLWd8mbDQqlxeWauGoviY0ez7+lN4F9vs8BQ==","signature_status":"signed_v1","signed_at":"2026-05-26T02:04:57.992412Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.11572","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b83416f3ed31c5ba1c662cfc32111bdaa359e6c455e01a04109ab07ba99f85ac","sha256:f9925ef99bd80a4d63240df948eafa85408e74d3d1ca3a3641a2c8d3677a1f76"],"state_sha256":"bc74827e65eaff855937a5b01eda73496b34a533289d14ed3e551dab9d467449"}