{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:HGVEQG3TR3LBGSQ5MP6QZW7HPE","short_pith_number":"pith:HGVEQG3T","canonical_record":{"source":{"id":"2111.05011","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-09T09:07:30Z","cross_cats_sorted":["cs.SD","eess.AS"],"title_canon_sha256":"894575fefa1b86e955be99e4b0e0d6f226a8a8d0c9a5c91f959c62a02ff50481","abstract_canon_sha256":"3a40563d988b0455a4a2d7363aa244878a27da56a618785b2a89e9dc431e8aee"},"schema_version":"1.0"},"canonical_sha256":"39aa481b738ed6134a1d63fd0cdbe7790615e12743c2c427deb1e3df091fae82","source":{"kind":"arxiv","id":"2111.05011","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.05011","created_at":"2026-07-05T03:41:17Z"},{"alias_kind":"arxiv_version","alias_value":"2111.05011v2","created_at":"2026-07-05T03:41:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.05011","created_at":"2026-07-05T03:41:17Z"},{"alias_kind":"pith_short_12","alias_value":"HGVEQG3TR3LB","created_at":"2026-07-05T03:41:17Z"},{"alias_kind":"pith_short_16","alias_value":"HGVEQG3TR3LBGSQ5","created_at":"2026-07-05T03:41:17Z"},{"alias_kind":"pith_short_8","alias_value":"HGVEQG3T","created_at":"2026-07-05T03:41:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:HGVEQG3TR3LBGSQ5MP6QZW7HPE","target":"record","payload":{"canonical_record":{"source":{"id":"2111.05011","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-09T09:07:30Z","cross_cats_sorted":["cs.SD","eess.AS"],"title_canon_sha256":"894575fefa1b86e955be99e4b0e0d6f226a8a8d0c9a5c91f959c62a02ff50481","abstract_canon_sha256":"3a40563d988b0455a4a2d7363aa244878a27da56a618785b2a89e9dc431e8aee"},"schema_version":"1.0"},"canonical_sha256":"39aa481b738ed6134a1d63fd0cdbe7790615e12743c2c427deb1e3df091fae82","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:41:17.097163Z","signature_b64":"9zI4asq+1o80RBKWBkhhikeobaHHVP8p6Oq6R5S1qBv7lprBKhbLQ9sZqYY2kvCQ0bb9UdAY+wyHoVa3ekLCCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"39aa481b738ed6134a1d63fd0cdbe7790615e12743c2c427deb1e3df091fae82","last_reissued_at":"2026-07-05T03:41:17.096675Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:41:17.096675Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2111.05011","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:41:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gKABd+3EEowFE3K46TnXVpC2Eqaw6VFJaOaZiMc2CVA0NITJNwCa82JTITgYbW3kB54oFAHLvaVYIDljJAANCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-25T05:15:20.811645Z"},"content_sha256":"de2180fd935b5c8857c8895cebed8ea2678c6542eaa61df5497615ad7c8c3e71","schema_version":"1.0","event_id":"sha256:de2180fd935b5c8857c8895cebed8ea2678c6542eaa61df5497615ad7c8c3e71"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:HGVEQG3TR3LBGSQ5MP6QZW7HPE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RAVE: A variational autoencoder for fast and high-quality neural audio synthesis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SD","eess.AS"],"primary_cat":"cs.LG","authors_text":"Antoine Caillon, Philippe Esling","submitted_at":"2021-11-09T09:07:30Z","abstract_excerpt":"Deep generative models applied to audio have improved by a large margin the state-of-the-art in many speech and music related tasks. However, as raw waveform modelling remains an inherently difficult task, audio generative models are either computationally intensive, rely on low sampling rates, are complicated to control or restrict the nature of possible signals. Among those models, Variational AutoEncoders (VAE) give control over the generation by exposing latent variables, although they usually suffer from low synthesis quality. In this paper, we introduce a Realtime Audio Variational autoE"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.05011","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2111.05011/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:41:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V96zZiwfRyKYJTmK0V1SKmR+ir6Eki26IRitm8WWwCAf5EobwbrQyBaRnl4Hj9nz7UFRyx8r0+QDG2rxZaM4BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-25T05:15:20.812013Z"},"content_sha256":"2e7b3df2a9da2f47587b429bf40156db4f62be71cbb3d1f88f68b4fd2c7ed4b5","schema_version":"1.0","event_id":"sha256:2e7b3df2a9da2f47587b429bf40156db4f62be71cbb3d1f88f68b4fd2c7ed4b5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HGVEQG3TR3LBGSQ5MP6QZW7HPE/bundle.json","state_url":"https://pith.science/pith/HGVEQG3TR3LBGSQ5MP6QZW7HPE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HGVEQG3TR3LBGSQ5MP6QZW7HPE/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-25T05:15:20Z","links":{"resolver":"https://pith.science/pith/HGVEQG3TR3LBGSQ5MP6QZW7HPE","bundle":"https://pith.science/pith/HGVEQG3TR3LBGSQ5MP6QZW7HPE/bundle.json","state":"https://pith.science/pith/HGVEQG3TR3LBGSQ5MP6QZW7HPE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HGVEQG3TR3LBGSQ5MP6QZW7HPE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:HGVEQG3TR3LBGSQ5MP6QZW7HPE","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":"3a40563d988b0455a4a2d7363aa244878a27da56a618785b2a89e9dc431e8aee","cross_cats_sorted":["cs.SD","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-09T09:07:30Z","title_canon_sha256":"894575fefa1b86e955be99e4b0e0d6f226a8a8d0c9a5c91f959c62a02ff50481"},"schema_version":"1.0","source":{"id":"2111.05011","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.05011","created_at":"2026-07-05T03:41:17Z"},{"alias_kind":"arxiv_version","alias_value":"2111.05011v2","created_at":"2026-07-05T03:41:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.05011","created_at":"2026-07-05T03:41:17Z"},{"alias_kind":"pith_short_12","alias_value":"HGVEQG3TR3LB","created_at":"2026-07-05T03:41:17Z"},{"alias_kind":"pith_short_16","alias_value":"HGVEQG3TR3LBGSQ5","created_at":"2026-07-05T03:41:17Z"},{"alias_kind":"pith_short_8","alias_value":"HGVEQG3T","created_at":"2026-07-05T03:41:17Z"}],"graph_snapshots":[{"event_id":"sha256:2e7b3df2a9da2f47587b429bf40156db4f62be71cbb3d1f88f68b4fd2c7ed4b5","target":"graph","created_at":"2026-07-05T03:41:17Z","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/2111.05011/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep generative models applied to audio have improved by a large margin the state-of-the-art in many speech and music related tasks. However, as raw waveform modelling remains an inherently difficult task, audio generative models are either computationally intensive, rely on low sampling rates, are complicated to control or restrict the nature of possible signals. Among those models, Variational AutoEncoders (VAE) give control over the generation by exposing latent variables, although they usually suffer from low synthesis quality. In this paper, we introduce a Realtime Audio Variational autoE","authors_text":"Antoine Caillon, Philippe Esling","cross_cats":["cs.SD","eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-09T09:07:30Z","title":"RAVE: A variational autoencoder for fast and high-quality neural audio synthesis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.05011","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:de2180fd935b5c8857c8895cebed8ea2678c6542eaa61df5497615ad7c8c3e71","target":"record","created_at":"2026-07-05T03:41:17Z","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":"3a40563d988b0455a4a2d7363aa244878a27da56a618785b2a89e9dc431e8aee","cross_cats_sorted":["cs.SD","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-09T09:07:30Z","title_canon_sha256":"894575fefa1b86e955be99e4b0e0d6f226a8a8d0c9a5c91f959c62a02ff50481"},"schema_version":"1.0","source":{"id":"2111.05011","kind":"arxiv","version":2}},"canonical_sha256":"39aa481b738ed6134a1d63fd0cdbe7790615e12743c2c427deb1e3df091fae82","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"39aa481b738ed6134a1d63fd0cdbe7790615e12743c2c427deb1e3df091fae82","first_computed_at":"2026-07-05T03:41:17.096675Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:41:17.096675Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9zI4asq+1o80RBKWBkhhikeobaHHVP8p6Oq6R5S1qBv7lprBKhbLQ9sZqYY2kvCQ0bb9UdAY+wyHoVa3ekLCCg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:41:17.097163Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.05011","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:de2180fd935b5c8857c8895cebed8ea2678c6542eaa61df5497615ad7c8c3e71","sha256:2e7b3df2a9da2f47587b429bf40156db4f62be71cbb3d1f88f68b4fd2c7ed4b5"],"state_sha256":"fe283e58b62cb4064fa35c7bdbb6ee5fd57327d6254209d286cc08ad908a2d22"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fRf+AkAK9MVWVOBUIQ6xvqbvdwW3kZzVQY/+kHO2Q01uHcaBaHmUAa4hz/B526osaeNrSQN1U7jifej2md2zCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-25T05:15:20.814159Z","bundle_sha256":"bc95aa5742acd899c5fa8b9c242d235d40a3122ef68566ce7f6aa1a6d4f7b2bf"}}