{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:FDYW63LKEFRKACQBZHAEJQRVC4","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":"e6475ed7a1314f9b3bb07256ea16a938c09594cdbd531e226261ba0a6c2f666a","cross_cats_sorted":["cs.AI","eess.AS"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.SD","submitted_at":"2024-08-23T20:03:51Z","title_canon_sha256":"88a5bde9901698338a717366cb19e28d331be29026d276e81d331f36b0ac9c13"},"schema_version":"1.0","source":{"id":"2408.13355","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.13355","created_at":"2026-07-05T08:58:49Z"},{"alias_kind":"arxiv_version","alias_value":"2408.13355v1","created_at":"2026-07-05T08:58:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.13355","created_at":"2026-07-05T08:58:49Z"},{"alias_kind":"pith_short_12","alias_value":"FDYW63LKEFRK","created_at":"2026-07-05T08:58:49Z"},{"alias_kind":"pith_short_16","alias_value":"FDYW63LKEFRKACQB","created_at":"2026-07-05T08:58:49Z"},{"alias_kind":"pith_short_8","alias_value":"FDYW63LK","created_at":"2026-07-05T08:58:49Z"}],"graph_snapshots":[{"event_id":"sha256:37bfc00d6cbf450f20905c57d0dcc65e454ecb9e508d7c85a5a6d09cd46f88b5","target":"graph","created_at":"2026-07-05T08:58:49Z","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/2408.13355/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A keyword spotting (KWS) engine that is continuously running on device is exposed to various speech signals that are usually unseen before. It is a challenging problem to build a small-footprint and high-performing KWS model with robustness under different acoustic environments. In this paper, we explore how to effectively apply adversarial examples to improve KWS robustness. We propose datasource-aware disentangled learning with adversarial examples to reduce the mismatch between the original and adversarial data as well as the mismatch across original training datasources. The KWS model arch","authors_text":"Biqiao Zhang, Li Wan, Ming Sun, Shang-Wen Li, Xin Lei, Yiteng Huang, Zhaojun Yang, Zhenyu Wang","cross_cats":["cs.AI","eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.SD","submitted_at":"2024-08-23T20:03:51Z","title":"Disentangled Training with Adversarial Examples For Robust Small-footprint Keyword Spotting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.13355","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":"sha256:1bc47e5e2f3f14b24b0b40accdbf66724fefd4dc1d5df3124c57926ba7543a1b","target":"record","created_at":"2026-07-05T08:58:49Z","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":"e6475ed7a1314f9b3bb07256ea16a938c09594cdbd531e226261ba0a6c2f666a","cross_cats_sorted":["cs.AI","eess.AS"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.SD","submitted_at":"2024-08-23T20:03:51Z","title_canon_sha256":"88a5bde9901698338a717366cb19e28d331be29026d276e81d331f36b0ac9c13"},"schema_version":"1.0","source":{"id":"2408.13355","kind":"arxiv","version":1}},"canonical_sha256":"28f16f6d6a2162a00a01c9c044c23517159b967c835e2f83a585db76b2db7d69","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"28f16f6d6a2162a00a01c9c044c23517159b967c835e2f83a585db76b2db7d69","first_computed_at":"2026-07-05T08:58:49.269641Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:58:49.269641Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6KfjOzIGs3D8U3L38IAcYLs+AiEWm3gR2D8fy+akwDZelq5lAVNKkiIjW5x9yf2lzFyhNA37+AfYZ2cUTQN5Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:58:49.270243Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.13355","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1bc47e5e2f3f14b24b0b40accdbf66724fefd4dc1d5df3124c57926ba7543a1b","sha256:37bfc00d6cbf450f20905c57d0dcc65e454ecb9e508d7c85a5a6d09cd46f88b5"],"state_sha256":"92e90f36dbd8223f658382289d6d5de48270f56d053f4bc242afa448d9b0f39a"}