{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:52ZUNSUBPORFPX7SX6VE5QJHG2","short_pith_number":"pith:52ZUNSUB","schema_version":"1.0","canonical_sha256":"eeb346ca817ba257dff2bfaa4ec12736a416f55ad6a055751c705ae97b56fd81","source":{"kind":"arxiv","id":"2312.08293","version":2},"attestation_state":"computed","paper":{"title":"Model-Free Verification for Neural Network Controlled Systems","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Antonis Papachristodoulou, Han Wang, Liqun Zhao, Zuxun Xiong","submitted_at":"2023-12-13T17:10:32Z","abstract_excerpt":"Neural network controllers have shown potential in achieving superior performance in feedback control systems. Although a neural network can be trained efficiently using deep and reinforcement learning methods, providing formal guarantees for the closed-loop properties is challenging. The main difficulty comes from the nonlinear activation functions. One popular method is to use sector bounds on the activation functions resulting in a robust analysis. These methods work well under the assumption that the system dynamics are perfectly known, which is, however, impossible in practice. In this pa"},"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":"2312.08293","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"math.OC","submitted_at":"2023-12-13T17:10:32Z","cross_cats_sorted":[],"title_canon_sha256":"fee3872e06ff60c7c32fec8a5c9e35f6d287fcb7be3904d1af444ed6424e2ef6","abstract_canon_sha256":"21695fe25d7f323d7e267e01b521bd1072f116672a27ae46ed4ae76a41f323f4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:31:35.872833Z","signature_b64":"VXXfpNbW5fuDI/1FPIwKGdYu8i4r0rV9ZQqdSFSAbUiS9v36WzBujPByezL/8kfVVCq3L7Po063fZbaNgt5XCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eeb346ca817ba257dff2bfaa4ec12736a416f55ad6a055751c705ae97b56fd81","last_reissued_at":"2026-07-05T07:31:35.872310Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:31:35.872310Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Model-Free Verification for Neural Network Controlled Systems","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Antonis Papachristodoulou, Han Wang, Liqun Zhao, Zuxun Xiong","submitted_at":"2023-12-13T17:10:32Z","abstract_excerpt":"Neural network controllers have shown potential in achieving superior performance in feedback control systems. Although a neural network can be trained efficiently using deep and reinforcement learning methods, providing formal guarantees for the closed-loop properties is challenging. The main difficulty comes from the nonlinear activation functions. One popular method is to use sector bounds on the activation functions resulting in a robust analysis. These methods work well under the assumption that the system dynamics are perfectly known, which is, however, impossible in practice. In this pa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.08293","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/2312.08293/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":"2312.08293","created_at":"2026-07-05T07:31:35.872380+00:00"},{"alias_kind":"arxiv_version","alias_value":"2312.08293v2","created_at":"2026-07-05T07:31:35.872380+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.08293","created_at":"2026-07-05T07:31:35.872380+00:00"},{"alias_kind":"pith_short_12","alias_value":"52ZUNSUBPORF","created_at":"2026-07-05T07:31:35.872380+00:00"},{"alias_kind":"pith_short_16","alias_value":"52ZUNSUBPORFPX7S","created_at":"2026-07-05T07:31:35.872380+00:00"},{"alias_kind":"pith_short_8","alias_value":"52ZUNSUB","created_at":"2026-07-05T07:31:35.872380+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/52ZUNSUBPORFPX7SX6VE5QJHG2","json":"https://pith.science/pith/52ZUNSUBPORFPX7SX6VE5QJHG2.json","graph_json":"https://pith.science/api/pith-number/52ZUNSUBPORFPX7SX6VE5QJHG2/graph.json","events_json":"https://pith.science/api/pith-number/52ZUNSUBPORFPX7SX6VE5QJHG2/events.json","paper":"https://pith.science/paper/52ZUNSUB"},"agent_actions":{"view_html":"https://pith.science/pith/52ZUNSUBPORFPX7SX6VE5QJHG2","download_json":"https://pith.science/pith/52ZUNSUBPORFPX7SX6VE5QJHG2.json","view_paper":"https://pith.science/paper/52ZUNSUB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2312.08293&json=true","fetch_graph":"https://pith.science/api/pith-number/52ZUNSUBPORFPX7SX6VE5QJHG2/graph.json","fetch_events":"https://pith.science/api/pith-number/52ZUNSUBPORFPX7SX6VE5QJHG2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/52ZUNSUBPORFPX7SX6VE5QJHG2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/52ZUNSUBPORFPX7SX6VE5QJHG2/action/storage_attestation","attest_author":"https://pith.science/pith/52ZUNSUBPORFPX7SX6VE5QJHG2/action/author_attestation","sign_citation":"https://pith.science/pith/52ZUNSUBPORFPX7SX6VE5QJHG2/action/citation_signature","submit_replication":"https://pith.science/pith/52ZUNSUBPORFPX7SX6VE5QJHG2/action/replication_record"}},"created_at":"2026-07-05T07:31:35.872380+00:00","updated_at":"2026-07-05T07:31:35.872380+00:00"}