{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:PX4VRG6A5O4YD4WAZBVPTU6ZPQ","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":"4aa87ae88de7499a852731c51825c01cbfa3f72321712014d44ab80ce8144abd","cross_cats_sorted":["cs.AI","cs.LG","cs.NE","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2022-11-03T14:20:32Z","title_canon_sha256":"aea8a0f5bb9f90f1d2a51722eb83d523622e71c8d1886b3f25e84ab901ed69e9"},"schema_version":"1.0","source":{"id":"2211.01839","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.01839","created_at":"2026-07-05T07:37:27Z"},{"alias_kind":"arxiv_version","alias_value":"2211.01839v2","created_at":"2026-07-05T07:37:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.01839","created_at":"2026-07-05T07:37:27Z"},{"alias_kind":"pith_short_12","alias_value":"PX4VRG6A5O4Y","created_at":"2026-07-05T07:37:27Z"},{"alias_kind":"pith_short_16","alias_value":"PX4VRG6A5O4YD4WA","created_at":"2026-07-05T07:37:27Z"},{"alias_kind":"pith_short_8","alias_value":"PX4VRG6A","created_at":"2026-07-05T07:37:27Z"}],"graph_snapshots":[{"event_id":"sha256:0c199fb51ff6d4ea6fc3942c5c624ffb7bc5b7eb370f1739f611d421294ab236","target":"graph","created_at":"2026-07-05T07:37:27Z","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/2211.01839/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Implicit neural representations (INRs) are a rapidly growing research field, which provides alternative ways to represent multimedia signals. Recent applications of INRs include image super-resolution, compression of high-dimensional signals, or 3D rendering. However, these solutions usually focus on visual data, and adapting them to the audio domain is not trivial. Moreover, it requires a separately trained model for every data sample. To address this limitation, we propose HyperSound, a meta-learning method leveraging hypernetworks to produce INRs for audio signals unseen at training time. W","authors_text":"Filip Szatkowski, Jacek Tabor, Karol J. Piczak, Przemys{\\l}aw Spurek, Tomasz Trzci\\'nski","cross_cats":["cs.AI","cs.LG","cs.NE","eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2022-11-03T14:20:32Z","title":"HyperSound: Generating Implicit Neural Representations of Audio Signals with Hypernetworks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.01839","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:b39783905b72f09980ccb56ee3bb26848555c8d1909ebd386c7264a6af7c42e8","target":"record","created_at":"2026-07-05T07:37:27Z","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":"4aa87ae88de7499a852731c51825c01cbfa3f72321712014d44ab80ce8144abd","cross_cats_sorted":["cs.AI","cs.LG","cs.NE","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SD","submitted_at":"2022-11-03T14:20:32Z","title_canon_sha256":"aea8a0f5bb9f90f1d2a51722eb83d523622e71c8d1886b3f25e84ab901ed69e9"},"schema_version":"1.0","source":{"id":"2211.01839","kind":"arxiv","version":2}},"canonical_sha256":"7df9589bc0ebb981f2c0c86af9d3d97c34ec8fe17da791f8b2f1f4523d5cfc9d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7df9589bc0ebb981f2c0c86af9d3d97c34ec8fe17da791f8b2f1f4523d5cfc9d","first_computed_at":"2026-07-05T07:37:27.777345Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:37:27.777345Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BkRDtDDZchbUoe/4ndEAJh0GSRNrg4Go+5wUr6i6EV7qhqFv0lJ62akuRsnaEQp+AZBgaIFmU01oAJbAR3kaCA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:37:27.777808Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.01839","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b39783905b72f09980ccb56ee3bb26848555c8d1909ebd386c7264a6af7c42e8","sha256:0c199fb51ff6d4ea6fc3942c5c624ffb7bc5b7eb370f1739f611d421294ab236"],"state_sha256":"13a97bc51fce0ecc7da3b7bc43d4d56e003b40c766aa7941772427bac4f23c49"}