{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:XASQI6KUAFV7SWRJ5T62BZZWTN","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"e299d21b6833b583d219b4743e3c7d982f703d235c98f7995ecdb9a854ec46cb","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-02T00:41:24Z","title_canon_sha256":"7eada99f4c5bf0315fd89539fe91b43f4506761c1cf6d9bf46cdebf7ee587071"},"schema_version":"1.0","source":{"id":"2506.01230","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.01230","created_at":"2026-07-05T11:14:10Z"},{"alias_kind":"arxiv_version","alias_value":"2506.01230v1","created_at":"2026-07-05T11:14:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01230","created_at":"2026-07-05T11:14:10Z"},{"alias_kind":"pith_short_12","alias_value":"XASQI6KUAFV7","created_at":"2026-07-05T11:14:10Z"},{"alias_kind":"pith_short_16","alias_value":"XASQI6KUAFV7SWRJ","created_at":"2026-07-05T11:14:10Z"},{"alias_kind":"pith_short_8","alias_value":"XASQI6KU","created_at":"2026-07-05T11:14:10Z"}],"graph_snapshots":[{"event_id":"sha256:83571e59c2d594ac0f88d34250af2a89c5c88390d225a39b0315aa2283f64ce9","target":"graph","created_at":"2026-07-05T11:14:10Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2506.01230/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Structured data-quality issues, such as missing values correlated with demographics, culturally biased labels, or systemic selection biases, routinely degrade the reliability of machine-learning pipelines. Regulators now increasingly demand evidence that high-stakes systems can withstand these realistic, interdependent errors, yet current robustness evaluations typically use random or overly simplistic corruptions, leaving worst-case scenarios unexplored. We introduce SAVAGE, a causally inspired framework that (i) formally models realistic data-quality issues through dependency graphs and flex","authors_text":"Babak Salimi, Boris Glavic, Felipe Lorenzi, Geyang Xu, Jiongli Zhu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-02T00:41:24Z","title":"Stress-Testing ML Pipelines with Adversarial Data Corruption"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01230","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:426220ea05b32431a845ba1ee794b5ced595dcd3ddae5d29d7925db42b856878","target":"record","created_at":"2026-07-05T11:14:10Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"e299d21b6833b583d219b4743e3c7d982f703d235c98f7995ecdb9a854ec46cb","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-02T00:41:24Z","title_canon_sha256":"7eada99f4c5bf0315fd89539fe91b43f4506761c1cf6d9bf46cdebf7ee587071"},"schema_version":"1.0","source":{"id":"2506.01230","kind":"arxiv","version":1}},"canonical_sha256":"b825047954016bf95a29ecfda0e7369b74023170d80031d7519e5d9464b5cae7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b825047954016bf95a29ecfda0e7369b74023170d80031d7519e5d9464b5cae7","first_computed_at":"2026-07-05T11:14:10.164739Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:14:10.164739Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Sl7DcF233u48kJaqS76Z9iLJY9xBPkY3sxGUlxd+eGxPGWT1zknhsX0nQJdYGvaSrhH+b6VB30XeYAOkbmqADA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:14:10.165203Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.01230","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:426220ea05b32431a845ba1ee794b5ced595dcd3ddae5d29d7925db42b856878","sha256:83571e59c2d594ac0f88d34250af2a89c5c88390d225a39b0315aa2283f64ce9"],"state_sha256":"edc260558a4f6748850257d259655890f8a3efa0157e8e85bd2a45d72d817c3e"}