{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:5FZQDVWYBJJATTL4OFAORRPF45","short_pith_number":"pith:5FZQDVWY","schema_version":"1.0","canonical_sha256":"e97301d6d80a5209cd7c7140e8c5e5e74c4d2cffaee38b8a12f7c40789388bf9","source":{"kind":"arxiv","id":"2209.10034","version":2},"attestation_state":"computed","paper":{"title":"Differentiable Safe Controller Design through Control Barrier Functions","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","cs.SY"],"primary_cat":"eess.SY","authors_text":"Rahul Mangharam, Shaoru Chen, Shuo Yang, Victor M. Preciado","submitted_at":"2022-09-20T23:03:22Z","abstract_excerpt":"Learning-based controllers, such as neural network (NN) controllers, can show high empirical performance but lack formal safety guarantees. To address this issue, control barrier functions (CBFs) have been applied as a safety filter to monitor and modify the outputs of learning-based controllers in order to guarantee the safety of the closed-loop system. However, such modification can be myopic with unpredictable long-term effects. In this work, we propose a safe-by-construction NN controller which employs differentiable CBF-based safety layers, and investigate the performance of safe-by-const"},"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":"2209.10034","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2022-09-20T23:03:22Z","cross_cats_sorted":["cs.LG","cs.SY"],"title_canon_sha256":"2b32b835f302a994cbd8a61df681b1c7902699edca13859fd6c7bb409350d023","abstract_canon_sha256":"1258a021a4260180545007c161ae59a9eea4a761357035e74c02a7d3ecf58049"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:31:35.151030Z","signature_b64":"t4D0JERPkgvHJIiN+4ZGTq5PB0IMoMVtj664EO9AwgWyGuh2l/qkn8Op4XINWRbP2QZ0tZ7+nWcJiqudvsBJDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e97301d6d80a5209cd7c7140e8c5e5e74c4d2cffaee38b8a12f7c40789388bf9","last_reissued_at":"2026-07-05T05:31:35.150611Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:31:35.150611Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Differentiable Safe Controller Design through Control Barrier Functions","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","cs.SY"],"primary_cat":"eess.SY","authors_text":"Rahul Mangharam, Shaoru Chen, Shuo Yang, Victor M. Preciado","submitted_at":"2022-09-20T23:03:22Z","abstract_excerpt":"Learning-based controllers, such as neural network (NN) controllers, can show high empirical performance but lack formal safety guarantees. To address this issue, control barrier functions (CBFs) have been applied as a safety filter to monitor and modify the outputs of learning-based controllers in order to guarantee the safety of the closed-loop system. However, such modification can be myopic with unpredictable long-term effects. In this work, we propose a safe-by-construction NN controller which employs differentiable CBF-based safety layers, and investigate the performance of safe-by-const"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.10034","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/2209.10034/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":"2209.10034","created_at":"2026-07-05T05:31:35.150673+00:00"},{"alias_kind":"arxiv_version","alias_value":"2209.10034v2","created_at":"2026-07-05T05:31:35.150673+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.10034","created_at":"2026-07-05T05:31:35.150673+00:00"},{"alias_kind":"pith_short_12","alias_value":"5FZQDVWYBJJA","created_at":"2026-07-05T05:31:35.150673+00:00"},{"alias_kind":"pith_short_16","alias_value":"5FZQDVWYBJJATTL4","created_at":"2026-07-05T05:31:35.150673+00:00"},{"alias_kind":"pith_short_8","alias_value":"5FZQDVWY","created_at":"2026-07-05T05:31:35.150673+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/5FZQDVWYBJJATTL4OFAORRPF45","json":"https://pith.science/pith/5FZQDVWYBJJATTL4OFAORRPF45.json","graph_json":"https://pith.science/api/pith-number/5FZQDVWYBJJATTL4OFAORRPF45/graph.json","events_json":"https://pith.science/api/pith-number/5FZQDVWYBJJATTL4OFAORRPF45/events.json","paper":"https://pith.science/paper/5FZQDVWY"},"agent_actions":{"view_html":"https://pith.science/pith/5FZQDVWYBJJATTL4OFAORRPF45","download_json":"https://pith.science/pith/5FZQDVWYBJJATTL4OFAORRPF45.json","view_paper":"https://pith.science/paper/5FZQDVWY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2209.10034&json=true","fetch_graph":"https://pith.science/api/pith-number/5FZQDVWYBJJATTL4OFAORRPF45/graph.json","fetch_events":"https://pith.science/api/pith-number/5FZQDVWYBJJATTL4OFAORRPF45/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5FZQDVWYBJJATTL4OFAORRPF45/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5FZQDVWYBJJATTL4OFAORRPF45/action/storage_attestation","attest_author":"https://pith.science/pith/5FZQDVWYBJJATTL4OFAORRPF45/action/author_attestation","sign_citation":"https://pith.science/pith/5FZQDVWYBJJATTL4OFAORRPF45/action/citation_signature","submit_replication":"https://pith.science/pith/5FZQDVWYBJJATTL4OFAORRPF45/action/replication_record"}},"created_at":"2026-07-05T05:31:35.150673+00:00","updated_at":"2026-07-05T05:31:35.150673+00:00"}