{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:MGCFZ4CJRFMCWQ6JIR6KVOQ2KG","short_pith_number":"pith:MGCFZ4CJ","schema_version":"1.0","canonical_sha256":"61845cf04989582b43c9447caaba1a51a9bf2363d05032fef5a1a8abe1db2826","source":{"kind":"arxiv","id":"2507.15478","version":1},"attestation_state":"computed","paper":{"title":"The Constitutional Controller: Doubt-Calibrated Steering of Compliant Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.RO","authors_text":"Benedict Flade, Devendra Singh Dhami, Felix Divo, Julian Eggert, Kristian Kersting, Navid Hamid, Simon Kohaut","submitted_at":"2025-07-21T10:33:31Z","abstract_excerpt":"Ensuring reliable and rule-compliant behavior of autonomous agents in uncertain environments remains a fundamental challenge in modern robotics. Our work shows how neuro-symbolic systems, which integrate probabilistic, symbolic white-box reasoning models with deep learning methods, offer a powerful solution to this challenge. This enables the simultaneous consideration of explicit rules and neural models trained on noisy data, combining the strength of structured reasoning with flexible representations. To this end, we introduce the Constitutional Controller (CoCo), a novel framework designed "},"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":"2507.15478","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-07-21T10:33:31Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"9df138c6ff7915e4e7dd0ed0ef19a9cfd7e09d769b3dc22858c10c3dbae8b05c","abstract_canon_sha256":"d5fd593630af6df5250ea15ec62d79c01d3b7eeb2b9ceb5473f623e4ef83f79f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:40:37.816550Z","signature_b64":"PDFlBeHU9XtwxUKHrjzHOYg1CkG0JHBXixoW5BmVdtBv2tGNnF2l0z9oORvgCtHKh6r606DzF3fxxczYwoJuCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"61845cf04989582b43c9447caaba1a51a9bf2363d05032fef5a1a8abe1db2826","last_reissued_at":"2026-07-05T11:40:37.816054Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:40:37.816054Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The Constitutional Controller: Doubt-Calibrated Steering of Compliant Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.RO","authors_text":"Benedict Flade, Devendra Singh Dhami, Felix Divo, Julian Eggert, Kristian Kersting, Navid Hamid, Simon Kohaut","submitted_at":"2025-07-21T10:33:31Z","abstract_excerpt":"Ensuring reliable and rule-compliant behavior of autonomous agents in uncertain environments remains a fundamental challenge in modern robotics. Our work shows how neuro-symbolic systems, which integrate probabilistic, symbolic white-box reasoning models with deep learning methods, offer a powerful solution to this challenge. This enables the simultaneous consideration of explicit rules and neural models trained on noisy data, combining the strength of structured reasoning with flexible representations. To this end, we introduce the Constitutional Controller (CoCo), a novel framework designed "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.15478","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/2507.15478/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":"2507.15478","created_at":"2026-07-05T11:40:37.816109+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.15478v1","created_at":"2026-07-05T11:40:37.816109+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.15478","created_at":"2026-07-05T11:40:37.816109+00:00"},{"alias_kind":"pith_short_12","alias_value":"MGCFZ4CJRFMC","created_at":"2026-07-05T11:40:37.816109+00:00"},{"alias_kind":"pith_short_16","alias_value":"MGCFZ4CJRFMCWQ6J","created_at":"2026-07-05T11:40:37.816109+00:00"},{"alias_kind":"pith_short_8","alias_value":"MGCFZ4CJ","created_at":"2026-07-05T11:40:37.816109+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/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG","json":"https://pith.science/pith/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG.json","graph_json":"https://pith.science/api/pith-number/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG/graph.json","events_json":"https://pith.science/api/pith-number/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG/events.json","paper":"https://pith.science/paper/MGCFZ4CJ"},"agent_actions":{"view_html":"https://pith.science/pith/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG","download_json":"https://pith.science/pith/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG.json","view_paper":"https://pith.science/paper/MGCFZ4CJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.15478&json=true","fetch_graph":"https://pith.science/api/pith-number/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG/graph.json","fetch_events":"https://pith.science/api/pith-number/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG/action/storage_attestation","attest_author":"https://pith.science/pith/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG/action/author_attestation","sign_citation":"https://pith.science/pith/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG/action/citation_signature","submit_replication":"https://pith.science/pith/MGCFZ4CJRFMCWQ6JIR6KVOQ2KG/action/replication_record"}},"created_at":"2026-07-05T11:40:37.816109+00:00","updated_at":"2026-07-05T11:40:37.816109+00:00"}