{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:WP7CJY5GTWYF5XJ436WUMI6ZWL","short_pith_number":"pith:WP7CJY5G","schema_version":"1.0","canonical_sha256":"b3fe24e3a69db05edd3cdfad4623d9b2df1191deb0b470919831b366e51af433","source":{"kind":"arxiv","id":"2605.23274","version":1},"attestation_state":"computed","paper":{"title":"U-CESE: Unified Clip-based Event Search Engine for AI Challenge HCMC 2025","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Duc-Nhuan Le, Hoang-Phuc Nguyen, Minh-Hoang Le, Minh-Nhut Dang, Thanh-Duy Lam","submitted_at":"2026-05-22T06:28:41Z","abstract_excerpt":"Retrieving events from large-scale video datasets is challenging due to complex temporal, spatial, and multimodal information. This paper presents U-CESE, our solution for the AI Challenge HCMC 2025, a Unified Clip-based Event Search Engine for multimodal event retrieval across diverse video sources. Building on CESE, U-CESE integrates its three modules into a single cohesive framework, ensuring consistent processing and retrieval across query types. A core component is the Unified Clipping Algorithm, which merges separate clipping algorithms into one efficient pipeline. To handle large-scale "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.23274","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-22T06:28:41Z","cross_cats_sorted":[],"title_canon_sha256":"6b329a63d89e4c0aa66f9f189649c8708f38a393669ba04a330b28e5ca2497b2","abstract_canon_sha256":"7ae998b9db4ae42fd0c4be151aa06b200838289a42a7381af8f237b575125029"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-25T02:01:46.896333Z","signature_b64":"3pAlbwKOeA+MfT3N5qeqCtoQymzrxBig7/4M3MuEyB0mafack0y2Dwh2aHWUtpHncnFwa0Y6gjUf8IpnirtoCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b3fe24e3a69db05edd3cdfad4623d9b2df1191deb0b470919831b366e51af433","last_reissued_at":"2026-05-25T02:01:46.895818Z","signature_status":"signed_v1","first_computed_at":"2026-05-25T02:01:46.895818Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"U-CESE: Unified Clip-based Event Search Engine for AI Challenge HCMC 2025","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Duc-Nhuan Le, Hoang-Phuc Nguyen, Minh-Hoang Le, Minh-Nhut Dang, Thanh-Duy Lam","submitted_at":"2026-05-22T06:28:41Z","abstract_excerpt":"Retrieving events from large-scale video datasets is challenging due to complex temporal, spatial, and multimodal information. This paper presents U-CESE, our solution for the AI Challenge HCMC 2025, a Unified Clip-based Event Search Engine for multimodal event retrieval across diverse video sources. Building on CESE, U-CESE integrates its three modules into a single cohesive framework, ensuring consistent processing and retrieval across query types. A core component is the Unified Clipping Algorithm, which merges separate clipping algorithms into one efficient pipeline. To handle large-scale "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.23274","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/2605.23274/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.23274","created_at":"2026-05-25T02:01:46.895909+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.23274v1","created_at":"2026-05-25T02:01:46.895909+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.23274","created_at":"2026-05-25T02:01:46.895909+00:00"},{"alias_kind":"pith_short_12","alias_value":"WP7CJY5GTWYF","created_at":"2026-05-25T02:01:46.895909+00:00"},{"alias_kind":"pith_short_16","alias_value":"WP7CJY5GTWYF5XJ4","created_at":"2026-05-25T02:01:46.895909+00:00"},{"alias_kind":"pith_short_8","alias_value":"WP7CJY5G","created_at":"2026-05-25T02:01:46.895909+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WP7CJY5GTWYF5XJ436WUMI6ZWL","json":"https://pith.science/pith/WP7CJY5GTWYF5XJ436WUMI6ZWL.json","graph_json":"https://pith.science/api/pith-number/WP7CJY5GTWYF5XJ436WUMI6ZWL/graph.json","events_json":"https://pith.science/api/pith-number/WP7CJY5GTWYF5XJ436WUMI6ZWL/events.json","paper":"https://pith.science/paper/WP7CJY5G"},"agent_actions":{"view_html":"https://pith.science/pith/WP7CJY5GTWYF5XJ436WUMI6ZWL","download_json":"https://pith.science/pith/WP7CJY5GTWYF5XJ436WUMI6ZWL.json","view_paper":"https://pith.science/paper/WP7CJY5G","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.23274&json=true","fetch_graph":"https://pith.science/api/pith-number/WP7CJY5GTWYF5XJ436WUMI6ZWL/graph.json","fetch_events":"https://pith.science/api/pith-number/WP7CJY5GTWYF5XJ436WUMI6ZWL/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WP7CJY5GTWYF5XJ436WUMI6ZWL/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WP7CJY5GTWYF5XJ436WUMI6ZWL/action/storage_attestation","attest_author":"https://pith.science/pith/WP7CJY5GTWYF5XJ436WUMI6ZWL/action/author_attestation","sign_citation":"https://pith.science/pith/WP7CJY5GTWYF5XJ436WUMI6ZWL/action/citation_signature","submit_replication":"https://pith.science/pith/WP7CJY5GTWYF5XJ436WUMI6ZWL/action/replication_record"}},"created_at":"2026-05-25T02:01:46.895909+00:00","updated_at":"2026-05-25T02:01:46.895909+00:00"}