{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:MFRF2WM7XDPV7AMYMKEXUJCO2D","short_pith_number":"pith:MFRF2WM7","schema_version":"1.0","canonical_sha256":"61625d599fb8df5f819862897a244ed0d08ab18701ac75208831ff99d20aa1ff","source":{"kind":"arxiv","id":"2509.02025","version":1},"attestation_state":"computed","paper":{"title":"Curiosity-Driven Testing for Sequential Decision-Making Process","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Bowen Xu, Chengran Yang, David Lo, Jieke Shi, Junda He, Kisub Kim, Xin Zhou, Zhou Yang","submitted_at":"2025-09-02T07:14:46Z","abstract_excerpt":"Sequential decision-making processes (SDPs) are fundamental for complex real-world challenges, such as autonomous driving, robotic control, and traffic management. While recent advances in Deep Learning (DL) have led to mature solutions for solving these complex problems, SDMs remain vulnerable to learning unsafe behaviors, posing significant risks in safety-critical applications. However, developing a testing framework for SDMs that can identify a diverse set of crash-triggering scenarios remains an open challenge. To address this, we propose CureFuzz, a novel curiosity-driven black-box fuzz "},"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":"2509.02025","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2025-09-02T07:14:46Z","cross_cats_sorted":[],"title_canon_sha256":"445cb6e6cc2caec5495b2bb32c344058699588ce30339a675dd8c3cb4e50da46","abstract_canon_sha256":"f77c148fd2848458b8f5fcb15c7a5a801455b709fc15945b6064097ee7796ec8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:03:13.180322Z","signature_b64":"9i9OlQ53fJ5B2/SokBO1Q9ay50GnNnKOABlV683peoV9UNkHlXc+TQlQLNoZGx9aAghirGfJWbTmKaqeSZ2fDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"61625d599fb8df5f819862897a244ed0d08ab18701ac75208831ff99d20aa1ff","last_reissued_at":"2026-07-05T12:03:13.179887Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:03:13.179887Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Curiosity-Driven Testing for Sequential Decision-Making Process","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Bowen Xu, Chengran Yang, David Lo, Jieke Shi, Junda He, Kisub Kim, Xin Zhou, Zhou Yang","submitted_at":"2025-09-02T07:14:46Z","abstract_excerpt":"Sequential decision-making processes (SDPs) are fundamental for complex real-world challenges, such as autonomous driving, robotic control, and traffic management. While recent advances in Deep Learning (DL) have led to mature solutions for solving these complex problems, SDMs remain vulnerable to learning unsafe behaviors, posing significant risks in safety-critical applications. However, developing a testing framework for SDMs that can identify a diverse set of crash-triggering scenarios remains an open challenge. To address this, we propose CureFuzz, a novel curiosity-driven black-box fuzz "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.02025","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/2509.02025/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":"2509.02025","created_at":"2026-07-05T12:03:13.179946+00:00"},{"alias_kind":"arxiv_version","alias_value":"2509.02025v1","created_at":"2026-07-05T12:03:13.179946+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.02025","created_at":"2026-07-05T12:03:13.179946+00:00"},{"alias_kind":"pith_short_12","alias_value":"MFRF2WM7XDPV","created_at":"2026-07-05T12:03:13.179946+00:00"},{"alias_kind":"pith_short_16","alias_value":"MFRF2WM7XDPV7AMY","created_at":"2026-07-05T12:03:13.179946+00:00"},{"alias_kind":"pith_short_8","alias_value":"MFRF2WM7","created_at":"2026-07-05T12:03:13.179946+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/MFRF2WM7XDPV7AMYMKEXUJCO2D","json":"https://pith.science/pith/MFRF2WM7XDPV7AMYMKEXUJCO2D.json","graph_json":"https://pith.science/api/pith-number/MFRF2WM7XDPV7AMYMKEXUJCO2D/graph.json","events_json":"https://pith.science/api/pith-number/MFRF2WM7XDPV7AMYMKEXUJCO2D/events.json","paper":"https://pith.science/paper/MFRF2WM7"},"agent_actions":{"view_html":"https://pith.science/pith/MFRF2WM7XDPV7AMYMKEXUJCO2D","download_json":"https://pith.science/pith/MFRF2WM7XDPV7AMYMKEXUJCO2D.json","view_paper":"https://pith.science/paper/MFRF2WM7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2509.02025&json=true","fetch_graph":"https://pith.science/api/pith-number/MFRF2WM7XDPV7AMYMKEXUJCO2D/graph.json","fetch_events":"https://pith.science/api/pith-number/MFRF2WM7XDPV7AMYMKEXUJCO2D/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MFRF2WM7XDPV7AMYMKEXUJCO2D/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MFRF2WM7XDPV7AMYMKEXUJCO2D/action/storage_attestation","attest_author":"https://pith.science/pith/MFRF2WM7XDPV7AMYMKEXUJCO2D/action/author_attestation","sign_citation":"https://pith.science/pith/MFRF2WM7XDPV7AMYMKEXUJCO2D/action/citation_signature","submit_replication":"https://pith.science/pith/MFRF2WM7XDPV7AMYMKEXUJCO2D/action/replication_record"}},"created_at":"2026-07-05T12:03:13.179946+00:00","updated_at":"2026-07-05T12:03:13.179946+00:00"}