{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:2CTB4IGYUJIN2YTEASCT4RAIYE","short_pith_number":"pith:2CTB4IGY","schema_version":"1.0","canonical_sha256":"d0a61e20d8a250dd626404853e4408c11edd7c746e9496220a3fbcebe2e22e7d","source":{"kind":"arxiv","id":"2606.18780","version":1},"attestation_state":"computed","paper":{"title":"SAMA: Semantic Anchor-aligned Augmentation for Unified Low-Resource Multimodal Information Extraction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.MM"],"primary_cat":"cs.CV","authors_text":"Chong Mu, Hui Gao, Jiazhou Pan, Ling Tian, Ming Jia, Quanjiang Guo, Zhao Kang","submitted_at":"2026-06-17T07:43:33Z","abstract_excerpt":"Multimodal Information Extraction (MIE)-covering tasks such as Multimodal Named Entity Recognition (MNER), Relation Extraction (MRE), and Event Extraction (MEE)-is essential for understanding multimedia content but remains constrained by severe data scarcity. Although data augmentation is a promising remedy, existing approaches are impeded by coarse cross-modal alignment and fragmented, task-specific designs that fail to exploit shared semantic knowledge. To overcome these limitations, we introduce Semantic Anchor-aligned Multimodal Augmentation (SAMA), a unified framework for generating high-"},"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":"2606.18780","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-17T07:43:33Z","cross_cats_sorted":["cs.CL","cs.MM"],"title_canon_sha256":"7697af9f3aab8a514c3086cc195fb397bc09040ac4a00091c96b68e19327bd2f","abstract_canon_sha256":"38237c27bbe9813e5aabfe2e9dae217a44b4f187e539b4e24d0ec17016a65866"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:11:47.079076Z","signature_b64":"YHSZT3JUUwiISZ5KUO9JKLGl3+K2i4oD7MVVryHyjcmdzc0DXhHPj43+Sf2o/5MDMXHWefH8oLm4BAlMADY3CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d0a61e20d8a250dd626404853e4408c11edd7c746e9496220a3fbcebe2e22e7d","last_reissued_at":"2026-06-19T16:11:47.078723Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:11:47.078723Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SAMA: Semantic Anchor-aligned Augmentation for Unified Low-Resource Multimodal Information Extraction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.MM"],"primary_cat":"cs.CV","authors_text":"Chong Mu, Hui Gao, Jiazhou Pan, Ling Tian, Ming Jia, Quanjiang Guo, Zhao Kang","submitted_at":"2026-06-17T07:43:33Z","abstract_excerpt":"Multimodal Information Extraction (MIE)-covering tasks such as Multimodal Named Entity Recognition (MNER), Relation Extraction (MRE), and Event Extraction (MEE)-is essential for understanding multimedia content but remains constrained by severe data scarcity. Although data augmentation is a promising remedy, existing approaches are impeded by coarse cross-modal alignment and fragmented, task-specific designs that fail to exploit shared semantic knowledge. To overcome these limitations, we introduce Semantic Anchor-aligned Multimodal Augmentation (SAMA), a unified framework for generating high-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.18780","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/2606.18780/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":"2606.18780","created_at":"2026-06-19T16:11:47.078784+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.18780v1","created_at":"2026-06-19T16:11:47.078784+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.18780","created_at":"2026-06-19T16:11:47.078784+00:00"},{"alias_kind":"pith_short_12","alias_value":"2CTB4IGYUJIN","created_at":"2026-06-19T16:11:47.078784+00:00"},{"alias_kind":"pith_short_16","alias_value":"2CTB4IGYUJIN2YTE","created_at":"2026-06-19T16:11:47.078784+00:00"},{"alias_kind":"pith_short_8","alias_value":"2CTB4IGY","created_at":"2026-06-19T16:11:47.078784+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/2CTB4IGYUJIN2YTEASCT4RAIYE","json":"https://pith.science/pith/2CTB4IGYUJIN2YTEASCT4RAIYE.json","graph_json":"https://pith.science/api/pith-number/2CTB4IGYUJIN2YTEASCT4RAIYE/graph.json","events_json":"https://pith.science/api/pith-number/2CTB4IGYUJIN2YTEASCT4RAIYE/events.json","paper":"https://pith.science/paper/2CTB4IGY"},"agent_actions":{"view_html":"https://pith.science/pith/2CTB4IGYUJIN2YTEASCT4RAIYE","download_json":"https://pith.science/pith/2CTB4IGYUJIN2YTEASCT4RAIYE.json","view_paper":"https://pith.science/paper/2CTB4IGY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.18780&json=true","fetch_graph":"https://pith.science/api/pith-number/2CTB4IGYUJIN2YTEASCT4RAIYE/graph.json","fetch_events":"https://pith.science/api/pith-number/2CTB4IGYUJIN2YTEASCT4RAIYE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2CTB4IGYUJIN2YTEASCT4RAIYE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2CTB4IGYUJIN2YTEASCT4RAIYE/action/storage_attestation","attest_author":"https://pith.science/pith/2CTB4IGYUJIN2YTEASCT4RAIYE/action/author_attestation","sign_citation":"https://pith.science/pith/2CTB4IGYUJIN2YTEASCT4RAIYE/action/citation_signature","submit_replication":"https://pith.science/pith/2CTB4IGYUJIN2YTEASCT4RAIYE/action/replication_record"}},"created_at":"2026-06-19T16:11:47.078784+00:00","updated_at":"2026-06-19T16:11:47.078784+00:00"}