{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:MKLHIQYTBSNPX63WYKVI7Q4GD6","short_pith_number":"pith:MKLHIQYT","canonical_record":{"source":{"id":"2406.04269","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-06-06T17:20:21Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"026db6cfe62fa1cbb71738fac7372efef8027ad26fc05a3fad521b33cf880c8e","abstract_canon_sha256":"d70c08d6901628356e2bc5b90e4393713d4de34e362c89d20364f3ab2d48994e"},"schema_version":"1.0"},"canonical_sha256":"62967443130c9afbfb76c2aa8fc3861fb526bf912dbc1d4c8c5385767861f3f3","source":{"kind":"arxiv","id":"2406.04269","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.04269","created_at":"2026-07-05T09:10:47Z"},{"alias_kind":"arxiv_version","alias_value":"2406.04269v1","created_at":"2026-07-05T09:10:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.04269","created_at":"2026-07-05T09:10:47Z"},{"alias_kind":"pith_short_12","alias_value":"MKLHIQYTBSNP","created_at":"2026-07-05T09:10:47Z"},{"alias_kind":"pith_short_16","alias_value":"MKLHIQYTBSNPX63W","created_at":"2026-07-05T09:10:47Z"},{"alias_kind":"pith_short_8","alias_value":"MKLHIQYT","created_at":"2026-07-05T09:10:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:MKLHIQYTBSNPX63WYKVI7Q4GD6","target":"record","payload":{"canonical_record":{"source":{"id":"2406.04269","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-06-06T17:20:21Z","cross_cats_sorted":["cs.SD"],"title_canon_sha256":"026db6cfe62fa1cbb71738fac7372efef8027ad26fc05a3fad521b33cf880c8e","abstract_canon_sha256":"d70c08d6901628356e2bc5b90e4393713d4de34e362c89d20364f3ab2d48994e"},"schema_version":"1.0"},"canonical_sha256":"62967443130c9afbfb76c2aa8fc3861fb526bf912dbc1d4c8c5385767861f3f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:10:47.932017Z","signature_b64":"741wYnq1Lh4Uvj/OkXl3Rfk+fE+McbcBL2B17ZmqbMb+ssPM26ZlEyqCEvBPynWoqBGjKsO73YYuSFkuzOTiBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"62967443130c9afbfb76c2aa8fc3861fb526bf912dbc1d4c8c5385767861f3f3","last_reissued_at":"2026-07-05T09:10:47.931468Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:10:47.931468Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.04269","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:10:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w1D3oHPvE5CFXH44REAs1u8AqNyHeabkyFRlv1VWPgtY4TV3IRbO223qGmTShgQtoFdEqjybijIJP5h9yK1xBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T21:52:09.530652Z"},"content_sha256":"f5c35c3aa533ff90c57aed20b83a62baf12f95f7c696dde1f7f243f84559fe28","schema_version":"1.0","event_id":"sha256:f5c35c3aa533ff90c57aed20b83a62baf12f95f7c696dde1f7f243f84559fe28"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:MKLHIQYTBSNPX63WYKVI7Q4GD6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Beyond Performance Plateaus: A Comprehensive Study on Scalability in Speech Enhancement","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SD"],"primary_cat":"eess.AS","authors_text":"Chenda Li, Jee-weon Jung, Kohei Saijo, Shinji Watanabe, Wangyou Zhang, Yanmin Qian","submitted_at":"2024-06-06T17:20:21Z","abstract_excerpt":"Deep learning-based speech enhancement (SE) models have achieved impressive performance in the past decade. Numerous advanced architectures have been designed to deliver state-of-the-art performance; however, their scalability potential remains unrevealed. Meanwhile, the majority of research focuses on small-sized datasets with restricted diversity, leading to a plateau in performance improvement. In this paper, we aim to provide new insights for addressing the above issues by exploring the scalability of SE models in terms of architectures, model sizes, compute budgets, and dataset sizes. Our"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.04269","kind":"arxiv","version":1},"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/2406.04269/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":"2026-07-05T09:10:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/FPsl+7FlLHjgjLce/wpuuJFMhlRig+yk8wHTyBEKqABZa9245H4LPq/H2/iiMCKo61fdSv5WhEPW3LRoHg+Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T21:52:09.531587Z"},"content_sha256":"5e65b53248a75699afd1503d6a00591ac03b0a8d05d07d65f6b72dae73a09756","schema_version":"1.0","event_id":"sha256:5e65b53248a75699afd1503d6a00591ac03b0a8d05d07d65f6b72dae73a09756"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MKLHIQYTBSNPX63WYKVI7Q4GD6/bundle.json","state_url":"https://pith.science/pith/MKLHIQYTBSNPX63WYKVI7Q4GD6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MKLHIQYTBSNPX63WYKVI7Q4GD6/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":"2026-08-16T21:52:09Z","links":{"resolver":"https://pith.science/pith/MKLHIQYTBSNPX63WYKVI7Q4GD6","bundle":"https://pith.science/pith/MKLHIQYTBSNPX63WYKVI7Q4GD6/bundle.json","state":"https://pith.science/pith/MKLHIQYTBSNPX63WYKVI7Q4GD6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MKLHIQYTBSNPX63WYKVI7Q4GD6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:MKLHIQYTBSNPX63WYKVI7Q4GD6","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":"d70c08d6901628356e2bc5b90e4393713d4de34e362c89d20364f3ab2d48994e","cross_cats_sorted":["cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-06-06T17:20:21Z","title_canon_sha256":"026db6cfe62fa1cbb71738fac7372efef8027ad26fc05a3fad521b33cf880c8e"},"schema_version":"1.0","source":{"id":"2406.04269","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.04269","created_at":"2026-07-05T09:10:47Z"},{"alias_kind":"arxiv_version","alias_value":"2406.04269v1","created_at":"2026-07-05T09:10:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.04269","created_at":"2026-07-05T09:10:47Z"},{"alias_kind":"pith_short_12","alias_value":"MKLHIQYTBSNP","created_at":"2026-07-05T09:10:47Z"},{"alias_kind":"pith_short_16","alias_value":"MKLHIQYTBSNPX63W","created_at":"2026-07-05T09:10:47Z"},{"alias_kind":"pith_short_8","alias_value":"MKLHIQYT","created_at":"2026-07-05T09:10:47Z"}],"graph_snapshots":[{"event_id":"sha256:5e65b53248a75699afd1503d6a00591ac03b0a8d05d07d65f6b72dae73a09756","target":"graph","created_at":"2026-07-05T09:10:47Z","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/2406.04269/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning-based speech enhancement (SE) models have achieved impressive performance in the past decade. Numerous advanced architectures have been designed to deliver state-of-the-art performance; however, their scalability potential remains unrevealed. Meanwhile, the majority of research focuses on small-sized datasets with restricted diversity, leading to a plateau in performance improvement. In this paper, we aim to provide new insights for addressing the above issues by exploring the scalability of SE models in terms of architectures, model sizes, compute budgets, and dataset sizes. Our","authors_text":"Chenda Li, Jee-weon Jung, Kohei Saijo, Shinji Watanabe, Wangyou Zhang, Yanmin Qian","cross_cats":["cs.SD"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-06-06T17:20:21Z","title":"Beyond Performance Plateaus: A Comprehensive Study on Scalability in Speech Enhancement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.04269","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:f5c35c3aa533ff90c57aed20b83a62baf12f95f7c696dde1f7f243f84559fe28","target":"record","created_at":"2026-07-05T09:10:47Z","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":"d70c08d6901628356e2bc5b90e4393713d4de34e362c89d20364f3ab2d48994e","cross_cats_sorted":["cs.SD"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2024-06-06T17:20:21Z","title_canon_sha256":"026db6cfe62fa1cbb71738fac7372efef8027ad26fc05a3fad521b33cf880c8e"},"schema_version":"1.0","source":{"id":"2406.04269","kind":"arxiv","version":1}},"canonical_sha256":"62967443130c9afbfb76c2aa8fc3861fb526bf912dbc1d4c8c5385767861f3f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"62967443130c9afbfb76c2aa8fc3861fb526bf912dbc1d4c8c5385767861f3f3","first_computed_at":"2026-07-05T09:10:47.931468Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:10:47.931468Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"741wYnq1Lh4Uvj/OkXl3Rfk+fE+McbcBL2B17ZmqbMb+ssPM26ZlEyqCEvBPynWoqBGjKsO73YYuSFkuzOTiBw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:10:47.932017Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.04269","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f5c35c3aa533ff90c57aed20b83a62baf12f95f7c696dde1f7f243f84559fe28","sha256:5e65b53248a75699afd1503d6a00591ac03b0a8d05d07d65f6b72dae73a09756"],"state_sha256":"49cd47de8184ca2fec8a24a0032ea7e2a9e26bfc66bf3b6d3e084d573401e714"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EpsCozzxtcPfGWngKeF1pE7kxk4HNAmTHRQ80qmFc+1Lhdwa52viuUNydZdCPU1XuJuNDvCRENv3B7K4KudsDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T21:52:09.539943Z","bundle_sha256":"ab1c9b5a97bb516dce04094b9e25e1bef75792441a1601e5c67224edf6586f9e"}}