{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:JGQ7UPH53G7VMU4B7EZK3PP3NN","short_pith_number":"pith:JGQ7UPH5","canonical_record":{"source":{"id":"2501.16542","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2025-01-27T22:26:37Z","cross_cats_sorted":["cs.LG","cs.SD"],"title_canon_sha256":"4823116a2a35975f6d35613761acd9fa7157a5264a8a33a5013f1546911f0cd6","abstract_canon_sha256":"8eeef69bfd1bef96deefe9b4cede751c705a44c80302aa2f3c5889d2abe11e1e"},"schema_version":"1.0"},"canonical_sha256":"49a1fa3cfdd9bf565381f932adbdfb6b5c475b908f1b2f8501587b4c333996a2","source":{"kind":"arxiv","id":"2501.16542","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.16542","created_at":"2026-07-05T10:06:14Z"},{"alias_kind":"arxiv_version","alias_value":"2501.16542v1","created_at":"2026-07-05T10:06:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.16542","created_at":"2026-07-05T10:06:14Z"},{"alias_kind":"pith_short_12","alias_value":"JGQ7UPH53G7V","created_at":"2026-07-05T10:06:14Z"},{"alias_kind":"pith_short_16","alias_value":"JGQ7UPH53G7VMU4B","created_at":"2026-07-05T10:06:14Z"},{"alias_kind":"pith_short_8","alias_value":"JGQ7UPH5","created_at":"2026-07-05T10:06:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:JGQ7UPH53G7VMU4B7EZK3PP3NN","target":"record","payload":{"canonical_record":{"source":{"id":"2501.16542","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2025-01-27T22:26:37Z","cross_cats_sorted":["cs.LG","cs.SD"],"title_canon_sha256":"4823116a2a35975f6d35613761acd9fa7157a5264a8a33a5013f1546911f0cd6","abstract_canon_sha256":"8eeef69bfd1bef96deefe9b4cede751c705a44c80302aa2f3c5889d2abe11e1e"},"schema_version":"1.0"},"canonical_sha256":"49a1fa3cfdd9bf565381f932adbdfb6b5c475b908f1b2f8501587b4c333996a2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:06:14.922427Z","signature_b64":"oB3KPdpxHbIHB/6ngTmoCIqKfHfJq9Jknm+hOrtxIODvpVsbp+7OWz2Pcw87FBFRKcGlB2IlOhu72X+UiqPQAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"49a1fa3cfdd9bf565381f932adbdfb6b5c475b908f1b2f8501587b4c333996a2","last_reissued_at":"2026-07-05T10:06:14.921893Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:06:14.921893Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.16542","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":"2026-07-05T10:06:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dIa783LbyeNORMgUVF3IegUM5P7KUvr/Mv0J683mrhlItD5AtaLK8MxuNw+cH/r+6ZvJdF3ezQv8jjVxicngAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T02:15:20.924473Z"},"content_sha256":"ae377e2ca69dfcf687c55e5749f3f3fc631a68d9b8671fcb2c8a5f3cdbb2be4f","schema_version":"1.0","event_id":"sha256:ae377e2ca69dfcf687c55e5749f3f3fc631a68d9b8671fcb2c8a5f3cdbb2be4f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:JGQ7UPH53G7VMU4B7EZK3PP3NN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"UniPET-SPK: A Unified Framework for Parameter-Efficient Tuning of Pre-trained Speech Models for Robust Speaker Verification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SD"],"primary_cat":"eess.AS","authors_text":"John H. L. Hansen, Mufan Sang","submitted_at":"2025-01-27T22:26:37Z","abstract_excerpt":"With excellent generalization ability, SSL speech models have shown impressive performance on various downstream tasks in the pre-training and fine-tuning paradigm. However, as the size of pre-trained models grows, fine-tuning becomes practically unfeasible due to expanding computation and storage requirements and the risk of overfitting. This study explores parameter-efficient tuning (PET) methods for adapting large-scale pre-trained SSL speech models to speaker verification task. Correspondingly, we propose three PET methods: (i)an adapter-tuning method, (ii)a prompt-tuning method, and (iii)"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.16542","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/2501.16542/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":"2026-07-05T10:06:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5hiITK2Eo4pZSptXwQDcsU4fxQ59cnJeZ8pxJk3NBvY3MEzjFWldXW6U9Iu/GCDewQSE9t0LU3vip8tOEOqmBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T02:15:20.925467Z"},"content_sha256":"2d2ceb8eebf50b84832ea3a018cce3fef9c75b188ec31251e0fb9ecc596a5a4e","schema_version":"1.0","event_id":"sha256:2d2ceb8eebf50b84832ea3a018cce3fef9c75b188ec31251e0fb9ecc596a5a4e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JGQ7UPH53G7VMU4B7EZK3PP3NN/bundle.json","state_url":"https://pith.science/pith/JGQ7UPH53G7VMU4B7EZK3PP3NN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JGQ7UPH53G7VMU4B7EZK3PP3NN/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":"2026-08-11T02:15:20Z","links":{"resolver":"https://pith.science/pith/JGQ7UPH53G7VMU4B7EZK3PP3NN","bundle":"https://pith.science/pith/JGQ7UPH53G7VMU4B7EZK3PP3NN/bundle.json","state":"https://pith.science/pith/JGQ7UPH53G7VMU4B7EZK3PP3NN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JGQ7UPH53G7VMU4B7EZK3PP3NN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:JGQ7UPH53G7VMU4B7EZK3PP3NN","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":"8eeef69bfd1bef96deefe9b4cede751c705a44c80302aa2f3c5889d2abe11e1e","cross_cats_sorted":["cs.LG","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2025-01-27T22:26:37Z","title_canon_sha256":"4823116a2a35975f6d35613761acd9fa7157a5264a8a33a5013f1546911f0cd6"},"schema_version":"1.0","source":{"id":"2501.16542","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.16542","created_at":"2026-07-05T10:06:14Z"},{"alias_kind":"arxiv_version","alias_value":"2501.16542v1","created_at":"2026-07-05T10:06:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.16542","created_at":"2026-07-05T10:06:14Z"},{"alias_kind":"pith_short_12","alias_value":"JGQ7UPH53G7V","created_at":"2026-07-05T10:06:14Z"},{"alias_kind":"pith_short_16","alias_value":"JGQ7UPH53G7VMU4B","created_at":"2026-07-05T10:06:14Z"},{"alias_kind":"pith_short_8","alias_value":"JGQ7UPH5","created_at":"2026-07-05T10:06:14Z"}],"graph_snapshots":[{"event_id":"sha256:2d2ceb8eebf50b84832ea3a018cce3fef9c75b188ec31251e0fb9ecc596a5a4e","target":"graph","created_at":"2026-07-05T10:06:14Z","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/2501.16542/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With excellent generalization ability, SSL speech models have shown impressive performance on various downstream tasks in the pre-training and fine-tuning paradigm. However, as the size of pre-trained models grows, fine-tuning becomes practically unfeasible due to expanding computation and storage requirements and the risk of overfitting. This study explores parameter-efficient tuning (PET) methods for adapting large-scale pre-trained SSL speech models to speaker verification task. Correspondingly, we propose three PET methods: (i)an adapter-tuning method, (ii)a prompt-tuning method, and (iii)","authors_text":"John H. L. Hansen, Mufan Sang","cross_cats":["cs.LG","cs.SD"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2025-01-27T22:26:37Z","title":"UniPET-SPK: A Unified Framework for Parameter-Efficient Tuning of Pre-trained Speech Models for Robust Speaker Verification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.16542","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:ae377e2ca69dfcf687c55e5749f3f3fc631a68d9b8671fcb2c8a5f3cdbb2be4f","target":"record","created_at":"2026-07-05T10:06:14Z","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":"8eeef69bfd1bef96deefe9b4cede751c705a44c80302aa2f3c5889d2abe11e1e","cross_cats_sorted":["cs.LG","cs.SD"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2025-01-27T22:26:37Z","title_canon_sha256":"4823116a2a35975f6d35613761acd9fa7157a5264a8a33a5013f1546911f0cd6"},"schema_version":"1.0","source":{"id":"2501.16542","kind":"arxiv","version":1}},"canonical_sha256":"49a1fa3cfdd9bf565381f932adbdfb6b5c475b908f1b2f8501587b4c333996a2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"49a1fa3cfdd9bf565381f932adbdfb6b5c475b908f1b2f8501587b4c333996a2","first_computed_at":"2026-07-05T10:06:14.921893Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:06:14.921893Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oB3KPdpxHbIHB/6ngTmoCIqKfHfJq9Jknm+hOrtxIODvpVsbp+7OWz2Pcw87FBFRKcGlB2IlOhu72X+UiqPQAA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:06:14.922427Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.16542","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ae377e2ca69dfcf687c55e5749f3f3fc631a68d9b8671fcb2c8a5f3cdbb2be4f","sha256:2d2ceb8eebf50b84832ea3a018cce3fef9c75b188ec31251e0fb9ecc596a5a4e"],"state_sha256":"afc1b37cfea8ad07e2ceaf29083fde3bba100bd04792737bb93fd75a20ed667d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X83ySfO323JTx3zse/p5T36FIfyRxldRFUuNJgvDlHHhMqZXqXo2UXe2qnsg30GCyLag27kZ7Z9DVOBtPiPZAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T02:15:20.931250Z","bundle_sha256":"58f07313c7231b7ee1217753b04c26d20014fb444daa021d2a83ce6982db773d"}}