{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:BUS4CMQFMIEHGVEBQIOG3I2CFA","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":"d4b406aba3a97b9d26942a27c1c49bfe676bfb92e79bc29afbfb762593687ae5","cross_cats_sorted":["cs.LG","eess.AS","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2025-01-17T19:56:22Z","title_canon_sha256":"cfc026e4b0876b84593c19ba084dbaefa08f12c0f8287ee849f9c0fe58e7e02d"},"schema_version":"1.0","source":{"id":"2501.10525","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.10525","created_at":"2026-07-05T10:04:22Z"},{"alias_kind":"arxiv_version","alias_value":"2501.10525v2","created_at":"2026-07-05T10:04:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.10525","created_at":"2026-07-05T10:04:22Z"},{"alias_kind":"pith_short_12","alias_value":"BUS4CMQFMIEH","created_at":"2026-07-05T10:04:22Z"},{"alias_kind":"pith_short_16","alias_value":"BUS4CMQFMIEHGVEB","created_at":"2026-07-05T10:04:22Z"},{"alias_kind":"pith_short_8","alias_value":"BUS4CMQF","created_at":"2026-07-05T10:04:22Z"}],"graph_snapshots":[{"event_id":"sha256:78675743e2595dfbd9d49bb44ea4620fc909831dbd04f45a6cbcb1e584ec42a1","target":"graph","created_at":"2026-07-05T10:04:22Z","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/2501.10525/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The DeepFilterNet (DFN) architecture was recently proposed as a deep learning model suited for hearing aid devices. Despite its competitive performance on numerous benchmarks, it still follows a `one-size-fits-all' approach, which aims to train a single, monolithic architecture that generalises across different noises and environments. However, its limited size and computation budget can hamper its generalisability. Recent work has shown that in-context adaptation can improve performance by conditioning the denoising process on additional information extracted from background recordings to mit","authors_text":"Andreas Triantafyllopoulos, Bj\\\"orn W. Schuller, Hendrik Schr\\\"oter, Iosif Tsangko, Michael M\\\"uller","cross_cats":["cs.LG","eess.AS","eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2025-01-17T19:56:22Z","title":"DFingerNet: Noise-Adaptive Speech Enhancement for Hearing Aids"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.10525","kind":"arxiv","version":2},"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:f8d50b81722359de3e16acb58c7cba525e1f99cab63f1831238883d500316b82","target":"record","created_at":"2026-07-05T10:04:22Z","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":"d4b406aba3a97b9d26942a27c1c49bfe676bfb92e79bc29afbfb762593687ae5","cross_cats_sorted":["cs.LG","eess.AS","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2025-01-17T19:56:22Z","title_canon_sha256":"cfc026e4b0876b84593c19ba084dbaefa08f12c0f8287ee849f9c0fe58e7e02d"},"schema_version":"1.0","source":{"id":"2501.10525","kind":"arxiv","version":2}},"canonical_sha256":"0d25c132056208735481821c6da342282ca3d0d6470833f78cc09b088e69cd8b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0d25c132056208735481821c6da342282ca3d0d6470833f78cc09b088e69cd8b","first_computed_at":"2026-07-05T10:04:22.572909Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:04:22.572909Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2P7I0L5RXkM4PavUVURuhzB+P+XpYh7+IWfHKuYwDvQdV5XhjnsFAxbEaWvtP1J6U+1h3OB3u0PU8kNLDrivAA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:04:22.573417Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.10525","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f8d50b81722359de3e16acb58c7cba525e1f99cab63f1831238883d500316b82","sha256:78675743e2595dfbd9d49bb44ea4620fc909831dbd04f45a6cbcb1e584ec42a1"],"state_sha256":"8d25e4c173fa3e102a624dbba0c4b4bcee5011a1f065b04745872b554fb7bfc9"}