{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:B7SSVL3PTUMEKLPMAWMMKUIKEN","short_pith_number":"pith:B7SSVL3P","schema_version":"1.0","canonical_sha256":"0fe52aaf6f9d18452dec0598c5510a234ffda5ca9569182bd22d6177ac104c96","source":{"kind":"arxiv","id":"2607.00654","version":1},"attestation_state":"computed","paper":{"title":"Linguistic Relative Policy Optimization for Video Anomaly Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Haosheng Chen, Jiankang Zheng, Jiaxu Leng, Ji Gan, Mengjingcheng Mo, Xinbo Gao, Zhanjie Wu","submitted_at":"2026-07-01T09:07:04Z","abstract_excerpt":"Video anomaly detection (VAD) with multimodal large language models has shown strong potential, yet most existing methods still depend on large-scale annotations or expert-designed priors, limiting their ability to acquire anomaly knowledge with as little human intervention as possible. To address this, we propose Linguistic Relative Policy Optimization (LRPO), which distills group-relative semantic advantages from multiple reasoning trajectories into a linguistically expressed anomaly experience prior, and adapts the model by injecting this prior into the context to steer its output distribut"},"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":"2607.00654","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-01T09:07:04Z","cross_cats_sorted":[],"title_canon_sha256":"406026b878f0d7e3fac9b5a67052d8ee5f6d6bb72fa1045cafcf903485b31062","abstract_canon_sha256":"87e4adae00504789a2889ee7177e218ebf3b8f021496d740a8f500a24fe2f2d1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-02T01:17:50.488711Z","signature_b64":"ANVTcp0j8m9dwkdoUGwv5zXgM1O2NT/0l+cGEalPkRJLfL0B80ovl51vnDsKZGptD4QxymqOrTcBqJsdnrRsCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0fe52aaf6f9d18452dec0598c5510a234ffda5ca9569182bd22d6177ac104c96","last_reissued_at":"2026-07-02T01:17:50.488274Z","signature_status":"signed_v1","first_computed_at":"2026-07-02T01:17:50.488274Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Linguistic Relative Policy Optimization for Video Anomaly Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Haosheng Chen, Jiankang Zheng, Jiaxu Leng, Ji Gan, Mengjingcheng Mo, Xinbo Gao, Zhanjie Wu","submitted_at":"2026-07-01T09:07:04Z","abstract_excerpt":"Video anomaly detection (VAD) with multimodal large language models has shown strong potential, yet most existing methods still depend on large-scale annotations or expert-designed priors, limiting their ability to acquire anomaly knowledge with as little human intervention as possible. To address this, we propose Linguistic Relative Policy Optimization (LRPO), which distills group-relative semantic advantages from multiple reasoning trajectories into a linguistically expressed anomaly experience prior, and adapts the model by injecting this prior into the context to steer its output distribut"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.00654","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/2607.00654/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":"2607.00654","created_at":"2026-07-02T01:17:50.488359+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.00654v1","created_at":"2026-07-02T01:17:50.488359+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.00654","created_at":"2026-07-02T01:17:50.488359+00:00"},{"alias_kind":"pith_short_12","alias_value":"B7SSVL3PTUME","created_at":"2026-07-02T01:17:50.488359+00:00"},{"alias_kind":"pith_short_16","alias_value":"B7SSVL3PTUMEKLPM","created_at":"2026-07-02T01:17:50.488359+00:00"},{"alias_kind":"pith_short_8","alias_value":"B7SSVL3P","created_at":"2026-07-02T01:17:50.488359+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/B7SSVL3PTUMEKLPMAWMMKUIKEN","json":"https://pith.science/pith/B7SSVL3PTUMEKLPMAWMMKUIKEN.json","graph_json":"https://pith.science/api/pith-number/B7SSVL3PTUMEKLPMAWMMKUIKEN/graph.json","events_json":"https://pith.science/api/pith-number/B7SSVL3PTUMEKLPMAWMMKUIKEN/events.json","paper":"https://pith.science/paper/B7SSVL3P"},"agent_actions":{"view_html":"https://pith.science/pith/B7SSVL3PTUMEKLPMAWMMKUIKEN","download_json":"https://pith.science/pith/B7SSVL3PTUMEKLPMAWMMKUIKEN.json","view_paper":"https://pith.science/paper/B7SSVL3P","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.00654&json=true","fetch_graph":"https://pith.science/api/pith-number/B7SSVL3PTUMEKLPMAWMMKUIKEN/graph.json","fetch_events":"https://pith.science/api/pith-number/B7SSVL3PTUMEKLPMAWMMKUIKEN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/B7SSVL3PTUMEKLPMAWMMKUIKEN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/B7SSVL3PTUMEKLPMAWMMKUIKEN/action/storage_attestation","attest_author":"https://pith.science/pith/B7SSVL3PTUMEKLPMAWMMKUIKEN/action/author_attestation","sign_citation":"https://pith.science/pith/B7SSVL3PTUMEKLPMAWMMKUIKEN/action/citation_signature","submit_replication":"https://pith.science/pith/B7SSVL3PTUMEKLPMAWMMKUIKEN/action/replication_record"}},"created_at":"2026-07-02T01:17:50.488359+00:00","updated_at":"2026-07-02T01:17:50.488359+00:00"}