{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:OZI6TUSOABZYTLGJQO4OIXMCHQ","short_pith_number":"pith:OZI6TUSO","schema_version":"1.0","canonical_sha256":"7651e9d24e007389acc983b8e45d823c0a590a867478f65539c8bebe19ca00ba","source":{"kind":"arxiv","id":"2503.18492","version":2},"attestation_state":"computed","paper":{"title":"VeriSafe Agent: Safeguarding Mobile GUI Agent via Logic-based Action Verification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.HC","authors_text":"Chihun Choi, Dongjae Lee, Insik Shin, Jaeyoung Wi, Jungjae Lee, Kihong Heo, Sangeun Oh, Sunjae Lee, Youngmin Im","submitted_at":"2025-03-24T09:46:05Z","abstract_excerpt":"Large Foundation Models (LFMs) have unlocked new possibilities in human-computer interaction, particularly with the rise of mobile Graphical User Interface (GUI) Agents capable of interacting with mobile GUIs. These agents allow users to automate complex mobile tasks through simple natural language instructions. However, the inherent probabilistic nature of LFMs, coupled with the ambiguity and context-dependence of mobile tasks, makes LFM-based automation unreliable and prone to errors. To address this critical challenge, we introduce VeriSafe Agent (VSA): a formal verification system that ser"},"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":"2503.18492","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-03-24T09:46:05Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"a3e9329d3db4a0e6c057f116375f64d7a54a87f31b5f2a22b93beb48000ed509","abstract_canon_sha256":"4ca901422bc038a1bc2bb1a1883404fd4f6c340d1456c4cbd4c29edb59904960"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:09:15.632077Z","signature_b64":"8wf5QKTHm+3XqGYKLX4Tanq2jOrK90XMexQi+LjIoVtLn2MIYrAA8HO6grk6W7VnGHEQjEEOz08uGSmO5E+IAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7651e9d24e007389acc983b8e45d823c0a590a867478f65539c8bebe19ca00ba","last_reissued_at":"2026-07-05T12:09:15.631531Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:09:15.631531Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"VeriSafe Agent: Safeguarding Mobile GUI Agent via Logic-based Action Verification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.HC","authors_text":"Chihun Choi, Dongjae Lee, Insik Shin, Jaeyoung Wi, Jungjae Lee, Kihong Heo, Sangeun Oh, Sunjae Lee, Youngmin Im","submitted_at":"2025-03-24T09:46:05Z","abstract_excerpt":"Large Foundation Models (LFMs) have unlocked new possibilities in human-computer interaction, particularly with the rise of mobile Graphical User Interface (GUI) Agents capable of interacting with mobile GUIs. These agents allow users to automate complex mobile tasks through simple natural language instructions. However, the inherent probabilistic nature of LFMs, coupled with the ambiguity and context-dependence of mobile tasks, makes LFM-based automation unreliable and prone to errors. To address this critical challenge, we introduce VeriSafe Agent (VSA): a formal verification system that ser"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.18492","kind":"arxiv","version":2},"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/2503.18492/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":"2503.18492","created_at":"2026-07-05T12:09:15.631590+00:00"},{"alias_kind":"arxiv_version","alias_value":"2503.18492v2","created_at":"2026-07-05T12:09:15.631590+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.18492","created_at":"2026-07-05T12:09:15.631590+00:00"},{"alias_kind":"pith_short_12","alias_value":"OZI6TUSOABZY","created_at":"2026-07-05T12:09:15.631590+00:00"},{"alias_kind":"pith_short_16","alias_value":"OZI6TUSOABZYTLGJ","created_at":"2026-07-05T12:09:15.631590+00:00"},{"alias_kind":"pith_short_8","alias_value":"OZI6TUSO","created_at":"2026-07-05T12:09:15.631590+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":3,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2505.03364","citing_title":"DroidRetriever: A Transparent and Steerable Automation System for Collaborative Mobile Information Seeking","ref_index":32,"is_internal_anchor":false},{"citing_arxiv_id":"2509.06477","citing_title":"MAS-Bench: A Unified Benchmark for Shortcut-Augmented Hybrid Mobile GUI Agents","ref_index":18,"is_internal_anchor":false},{"citing_arxiv_id":"2512.12634","citing_title":"MobiBench: Multi-Branch, Modular Benchmark for Mobile GUI Agents","ref_index":13,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/OZI6TUSOABZYTLGJQO4OIXMCHQ","json":"https://pith.science/pith/OZI6TUSOABZYTLGJQO4OIXMCHQ.json","graph_json":"https://pith.science/api/pith-number/OZI6TUSOABZYTLGJQO4OIXMCHQ/graph.json","events_json":"https://pith.science/api/pith-number/OZI6TUSOABZYTLGJQO4OIXMCHQ/events.json","paper":"https://pith.science/paper/OZI6TUSO"},"agent_actions":{"view_html":"https://pith.science/pith/OZI6TUSOABZYTLGJQO4OIXMCHQ","download_json":"https://pith.science/pith/OZI6TUSOABZYTLGJQO4OIXMCHQ.json","view_paper":"https://pith.science/paper/OZI6TUSO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2503.18492&json=true","fetch_graph":"https://pith.science/api/pith-number/OZI6TUSOABZYTLGJQO4OIXMCHQ/graph.json","fetch_events":"https://pith.science/api/pith-number/OZI6TUSOABZYTLGJQO4OIXMCHQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OZI6TUSOABZYTLGJQO4OIXMCHQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OZI6TUSOABZYTLGJQO4OIXMCHQ/action/storage_attestation","attest_author":"https://pith.science/pith/OZI6TUSOABZYTLGJQO4OIXMCHQ/action/author_attestation","sign_citation":"https://pith.science/pith/OZI6TUSOABZYTLGJQO4OIXMCHQ/action/citation_signature","submit_replication":"https://pith.science/pith/OZI6TUSOABZYTLGJQO4OIXMCHQ/action/replication_record"}},"created_at":"2026-07-05T12:09:15.631590+00:00","updated_at":"2026-07-05T12:09:15.631590+00:00"}