{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:LFLGCYRJT4IW7WWQD4DSS7QVTV","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":"5e9c61299d55a843bb8180d399d4abeb5b85ff0357daf4dcec6e805605c1786b","cross_cats_sorted":["cs.CR","cs.SD","eess.AS"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-05-31T15:58:37Z","title_canon_sha256":"0d7efe0dd25a97bd508fa702fb51525b920dd75c005958b8899e18f4d510406e"},"schema_version":"1.0","source":{"id":"2306.00044","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.00044","created_at":"2026-07-05T06:16:20Z"},{"alias_kind":"arxiv_version","alias_value":"2306.00044v1","created_at":"2026-07-05T06:16:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.00044","created_at":"2026-07-05T06:16:20Z"},{"alias_kind":"pith_short_12","alias_value":"LFLGCYRJT4IW","created_at":"2026-07-05T06:16:20Z"},{"alias_kind":"pith_short_16","alias_value":"LFLGCYRJT4IW7WWQ","created_at":"2026-07-05T06:16:20Z"},{"alias_kind":"pith_short_8","alias_value":"LFLGCYRJ","created_at":"2026-07-05T06:16:20Z"}],"graph_snapshots":[{"event_id":"sha256:78f123788ad4ad900761b5827bc34a96a46748d142f8606ab160dcab939e81eb","target":"graph","created_at":"2026-07-05T06:16:20Z","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/2306.00044/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Shortcut learning, or `Clever Hans effect` refers to situations where a learning agent (e.g., deep neural networks) learns spurious correlations present in data, resulting in biased models. We focus on finding shortcuts in deep learning based spoofing countermeasures (CMs) that predict whether a given utterance is spoofed or not. While prior work has addressed specific data artifacts, such as silence, no general normative framework has been explored for analyzing shortcut learning in CMs. In this study, we propose a generic approach to identifying shortcuts by introducing systematic interventi","authors_text":"Hye-Jin Shim, Md Sahidullah, Rosa Gonz\\'alez Hautam\\\"aki, Tomi Kinnunen","cross_cats":["cs.CR","cs.SD","eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-05-31T15:58:37Z","title":"How to Construct Perfect and Worse-than-Coin-Flip Spoofing Countermeasures: A Word of Warning on Shortcut Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.00044","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:db239f31c474670c62b992bcca537b3894d6e6b188c98f160e34a7e73b27cc3d","target":"record","created_at":"2026-07-05T06:16:20Z","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":"5e9c61299d55a843bb8180d399d4abeb5b85ff0357daf4dcec6e805605c1786b","cross_cats_sorted":["cs.CR","cs.SD","eess.AS"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-05-31T15:58:37Z","title_canon_sha256":"0d7efe0dd25a97bd508fa702fb51525b920dd75c005958b8899e18f4d510406e"},"schema_version":"1.0","source":{"id":"2306.00044","kind":"arxiv","version":1}},"canonical_sha256":"59566162299f116fdad01f07297e159d62b32838673b7a34517ee16d8a7224c4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"59566162299f116fdad01f07297e159d62b32838673b7a34517ee16d8a7224c4","first_computed_at":"2026-07-05T06:16:20.765067Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:16:20.765067Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QGaGDtalfJPR9+f0AqOY7E8kPuHBdaBoyhlSMSrUeJyskH9mR7UOqPQF05I2ieftWXv4VvJWIkuUJcPJPcNtCA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:16:20.765559Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.00044","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:db239f31c474670c62b992bcca537b3894d6e6b188c98f160e34a7e73b27cc3d","sha256:78f123788ad4ad900761b5827bc34a96a46748d142f8606ab160dcab939e81eb"],"state_sha256":"89bc4a05ec94259f45e8ba7969f222b93feda184fffaf4fe6410d7a78ce7ef0f"}