{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:LUCDT42KUPNB6XYXQPRVHN7QHL","short_pith_number":"pith:LUCDT42K","canonical_record":{"source":{"id":"2011.04491","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-11-09T15:16:29Z","cross_cats_sorted":["cs.CL","eess.AS"],"title_canon_sha256":"d0d728cb0096b7190b3dd6045e321190868d9f5d6719728d2a56a04f20018f37","abstract_canon_sha256":"904e7fd43ca921c3319c4769dd74e69e6b4fa3883bb3e5e2ea118bcf5f00ef66"},"schema_version":"1.0"},"canonical_sha256":"5d0439f34aa3da1f5f1783e353b7f03ad918abb6692ae4efedece69cdb329a91","source":{"kind":"arxiv","id":"2011.04491","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.04491","created_at":"2026-07-05T03:11:26Z"},{"alias_kind":"arxiv_version","alias_value":"2011.04491v2","created_at":"2026-07-05T03:11:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.04491","created_at":"2026-07-05T03:11:26Z"},{"alias_kind":"pith_short_12","alias_value":"LUCDT42KUPNB","created_at":"2026-07-05T03:11:26Z"},{"alias_kind":"pith_short_16","alias_value":"LUCDT42KUPNB6XYX","created_at":"2026-07-05T03:11:26Z"},{"alias_kind":"pith_short_8","alias_value":"LUCDT42K","created_at":"2026-07-05T03:11:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:LUCDT42KUPNB6XYXQPRVHN7QHL","target":"record","payload":{"canonical_record":{"source":{"id":"2011.04491","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-11-09T15:16:29Z","cross_cats_sorted":["cs.CL","eess.AS"],"title_canon_sha256":"d0d728cb0096b7190b3dd6045e321190868d9f5d6719728d2a56a04f20018f37","abstract_canon_sha256":"904e7fd43ca921c3319c4769dd74e69e6b4fa3883bb3e5e2ea118bcf5f00ef66"},"schema_version":"1.0"},"canonical_sha256":"5d0439f34aa3da1f5f1783e353b7f03ad918abb6692ae4efedece69cdb329a91","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:11:26.759208Z","signature_b64":"JsS+k/3/N1H3tjcTGtQY4y+EkFJ75PEvXXzoamXIFCYIpluh8rSMrsIbWK03cfYtjMXoBaclljhIV92ZuoYGDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5d0439f34aa3da1f5f1783e353b7f03ad918abb6692ae4efedece69cdb329a91","last_reissued_at":"2026-07-05T03:11:26.758769Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:11:26.758769Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2011.04491","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":"2026-07-05T03:11:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rec4nKGo2oOtNaocIJsdZR6GhSuQ+99jGuCWrIJhI17CQd76RfbtsOJKQLk8XTdO9dBr9Q/2AJGd1sE7UJOfCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T22:22:26.031593Z"},"content_sha256":"135d1a6ac00c3cb2bc77dafc08ed78b30eb98a3a2a6a93fe003ab7500df873a9","schema_version":"1.0","event_id":"sha256:135d1a6ac00c3cb2bc77dafc08ed78b30eb98a3a2a6a93fe003ab7500df873a9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:LUCDT42KUPNB6XYXQPRVHN7QHL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Masked Proxy Loss For Text-Independent Speaker Verification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","eess.AS"],"primary_cat":"cs.SD","authors_text":"Aiswarya Vinod Kumar, Bhiksha Raj, Hira Dhamyal, Jiachen Lian, Rita Singh","submitted_at":"2020-11-09T15:16:29Z","abstract_excerpt":"Open-set speaker recognition can be regarded as a metric learning problem, which is to maximize inter-class variance and minimize intra-class variance. Supervised metric learning can be categorized into entity-based learning and proxy-based learning. Most of the existing metric learning objectives like Contrastive, Triplet, Prototypical, GE2E, etc all belong to the former division, the performance of which is either highly dependent on sample mining strategy or restricted by insufficient label information in the mini-batch. Proxy-based losses mitigate both shortcomings, however, fine-grained c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.04491","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/2011.04491/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":"2026-07-05T03:11:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0r4+3gS3U4YYiaRe65TW/rer9oodCWPrK0L2k+5ZamfXV/Hgj6td9TnaGD6CdzTc8fN6n3qDpO4FjB/gvS2nAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T22:22:26.032177Z"},"content_sha256":"91a94b36cf2bb786895f76ae773ddcf84a065c38ed33331b49bc6767dc5bfc93","schema_version":"1.0","event_id":"sha256:91a94b36cf2bb786895f76ae773ddcf84a065c38ed33331b49bc6767dc5bfc93"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LUCDT42KUPNB6XYXQPRVHN7QHL/bundle.json","state_url":"https://pith.science/pith/LUCDT42KUPNB6XYXQPRVHN7QHL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LUCDT42KUPNB6XYXQPRVHN7QHL/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":"2026-08-20T22:22:26Z","links":{"resolver":"https://pith.science/pith/LUCDT42KUPNB6XYXQPRVHN7QHL","bundle":"https://pith.science/pith/LUCDT42KUPNB6XYXQPRVHN7QHL/bundle.json","state":"https://pith.science/pith/LUCDT42KUPNB6XYXQPRVHN7QHL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LUCDT42KUPNB6XYXQPRVHN7QHL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:LUCDT42KUPNB6XYXQPRVHN7QHL","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":"904e7fd43ca921c3319c4769dd74e69e6b4fa3883bb3e5e2ea118bcf5f00ef66","cross_cats_sorted":["cs.CL","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-11-09T15:16:29Z","title_canon_sha256":"d0d728cb0096b7190b3dd6045e321190868d9f5d6719728d2a56a04f20018f37"},"schema_version":"1.0","source":{"id":"2011.04491","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.04491","created_at":"2026-07-05T03:11:26Z"},{"alias_kind":"arxiv_version","alias_value":"2011.04491v2","created_at":"2026-07-05T03:11:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.04491","created_at":"2026-07-05T03:11:26Z"},{"alias_kind":"pith_short_12","alias_value":"LUCDT42KUPNB","created_at":"2026-07-05T03:11:26Z"},{"alias_kind":"pith_short_16","alias_value":"LUCDT42KUPNB6XYX","created_at":"2026-07-05T03:11:26Z"},{"alias_kind":"pith_short_8","alias_value":"LUCDT42K","created_at":"2026-07-05T03:11:26Z"}],"graph_snapshots":[{"event_id":"sha256:91a94b36cf2bb786895f76ae773ddcf84a065c38ed33331b49bc6767dc5bfc93","target":"graph","created_at":"2026-07-05T03:11:26Z","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/2011.04491/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Open-set speaker recognition can be regarded as a metric learning problem, which is to maximize inter-class variance and minimize intra-class variance. Supervised metric learning can be categorized into entity-based learning and proxy-based learning. Most of the existing metric learning objectives like Contrastive, Triplet, Prototypical, GE2E, etc all belong to the former division, the performance of which is either highly dependent on sample mining strategy or restricted by insufficient label information in the mini-batch. Proxy-based losses mitigate both shortcomings, however, fine-grained c","authors_text":"Aiswarya Vinod Kumar, Bhiksha Raj, Hira Dhamyal, Jiachen Lian, Rita Singh","cross_cats":["cs.CL","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-11-09T15:16:29Z","title":"Masked Proxy Loss For Text-Independent Speaker Verification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.04491","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":"sha256:135d1a6ac00c3cb2bc77dafc08ed78b30eb98a3a2a6a93fe003ab7500df873a9","target":"record","created_at":"2026-07-05T03:11:26Z","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":"904e7fd43ca921c3319c4769dd74e69e6b4fa3883bb3e5e2ea118bcf5f00ef66","cross_cats_sorted":["cs.CL","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-11-09T15:16:29Z","title_canon_sha256":"d0d728cb0096b7190b3dd6045e321190868d9f5d6719728d2a56a04f20018f37"},"schema_version":"1.0","source":{"id":"2011.04491","kind":"arxiv","version":2}},"canonical_sha256":"5d0439f34aa3da1f5f1783e353b7f03ad918abb6692ae4efedece69cdb329a91","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5d0439f34aa3da1f5f1783e353b7f03ad918abb6692ae4efedece69cdb329a91","first_computed_at":"2026-07-05T03:11:26.758769Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:11:26.758769Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JsS+k/3/N1H3tjcTGtQY4y+EkFJ75PEvXXzoamXIFCYIpluh8rSMrsIbWK03cfYtjMXoBaclljhIV92ZuoYGDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:11:26.759208Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.04491","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:135d1a6ac00c3cb2bc77dafc08ed78b30eb98a3a2a6a93fe003ab7500df873a9","sha256:91a94b36cf2bb786895f76ae773ddcf84a065c38ed33331b49bc6767dc5bfc93"],"state_sha256":"19e3725ed21d7f8743aba2d5923fa120b0ebbaf045de6a30692912b48a545e17"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Uw0tmHKLu2oxg+bgj+yMxb4JEntmIglebDkyae1be6Kw/jz9NFP5SQZ00LtSJ9FOTccf0+1luyqWYxWfenJ1CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T22:22:26.036020Z","bundle_sha256":"71ddb123ff4a5f17cef7dca1eab73c242153498cce1e357e02ad09a0ebf02537"}}