{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:U5MS422GV5KCPJTTNR3Z22UTR2","short_pith_number":"pith:U5MS422G","canonical_record":{"source":{"id":"2203.06849","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-03-14T04:26:40Z","cross_cats_sorted":["cs.SD","eess.AS"],"title_canon_sha256":"5ca1132542000f0ab641a1fd96938a3a6ab76b38b89d4d027ee7f77f31441737","abstract_canon_sha256":"dc5496529c1ebdf291c22fa8e97a19076f8d03e19754a23837f8acf9897009f0"},"schema_version":"1.0"},"canonical_sha256":"a7592e6b46af5427a6736c779d6a938ea25daa626a32777575d2cd186618d900","source":{"kind":"arxiv","id":"2203.06849","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.06849","created_at":"2026-07-05T04:04:56Z"},{"alias_kind":"arxiv_version","alias_value":"2203.06849v1","created_at":"2026-07-05T04:04:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.06849","created_at":"2026-07-05T04:04:56Z"},{"alias_kind":"pith_short_12","alias_value":"U5MS422GV5KC","created_at":"2026-07-05T04:04:56Z"},{"alias_kind":"pith_short_16","alias_value":"U5MS422GV5KCPJTT","created_at":"2026-07-05T04:04:56Z"},{"alias_kind":"pith_short_8","alias_value":"U5MS422G","created_at":"2026-07-05T04:04:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:U5MS422GV5KCPJTTNR3Z22UTR2","target":"record","payload":{"canonical_record":{"source":{"id":"2203.06849","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-03-14T04:26:40Z","cross_cats_sorted":["cs.SD","eess.AS"],"title_canon_sha256":"5ca1132542000f0ab641a1fd96938a3a6ab76b38b89d4d027ee7f77f31441737","abstract_canon_sha256":"dc5496529c1ebdf291c22fa8e97a19076f8d03e19754a23837f8acf9897009f0"},"schema_version":"1.0"},"canonical_sha256":"a7592e6b46af5427a6736c779d6a938ea25daa626a32777575d2cd186618d900","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:04:56.617999Z","signature_b64":"Kehvbv+wk6V/auV4vB/bJp3RI8c3eoTC5ByUj2JfoXuU94yQPLN1JXgzi17idYCNoWmHI6y67lvdP/wNc0bXCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a7592e6b46af5427a6736c779d6a938ea25daa626a32777575d2cd186618d900","last_reissued_at":"2026-07-05T04:04:56.617472Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:04:56.617472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.06849","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":"2026-07-05T04:04:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VD4gPSbFvRMArBhVWK+CdVO+PCGrAYV3NKhlgjAoj9RPHaiYRvB+t9nPttRf85y5Pi6NQUv4/TMRvWMpTEv1CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T19:36:56.149744Z"},"content_sha256":"2befc3b044787bdd42b43f1f9990f6e70644fdac569c482e1a7beb0d84d36548","schema_version":"1.0","event_id":"sha256:2befc3b044787bdd42b43f1f9990f6e70644fdac569c482e1a7beb0d84d36548"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:U5MS422GV5KCPJTTNR3Z22UTR2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SD","eess.AS"],"primary_cat":"cs.CL","authors_text":"Abdelrahman Mohamed, Andy T. Liu, Cheng-I Jeff Lai, Heng-Jui Chang, Hsiang-Sheng Tsai, Hsuan-Jui Chen, Hung-yi Lee, Jiatong Shi, Kushal Lakhotia, Phil Hall, Shang-Wen Li, Shinji Watanabe, Shu-wen Yang, Shuyan Dong, Wen-Chin Huang, Xuankai Chang, Zili Huang","submitted_at":"2022-03-14T04:26:40Z","abstract_excerpt":"Transfer learning has proven to be crucial in advancing the state of speech and natural language processing research in recent years. In speech, a model pre-trained by self-supervised learning transfers remarkably well on multiple tasks. However, the lack of a consistent evaluation methodology is limiting towards a holistic understanding of the efficacy of such models. SUPERB was a step towards introducing a common benchmark to evaluate pre-trained models across various speech tasks. In this paper, we introduce SUPERB-SG, a new benchmark focused on evaluating the semantic and generative capabi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.06849","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/2203.06849/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":"2026-07-05T04:04:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tVbJeDLRN1MVr0VdUCq0FOM0qlcU/5TSMQl4DsbGstH0Gd6AsU4UXo1K4STT9H/6/HN9Y3+HYQEYh1Q1wA9jAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T19:36:56.150114Z"},"content_sha256":"dae89d30cf8e15cb617416a778e932d0ee97d71409c0718403492aaccb7aa004","schema_version":"1.0","event_id":"sha256:dae89d30cf8e15cb617416a778e932d0ee97d71409c0718403492aaccb7aa004"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/U5MS422GV5KCPJTTNR3Z22UTR2/bundle.json","state_url":"https://pith.science/pith/U5MS422GV5KCPJTTNR3Z22UTR2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/U5MS422GV5KCPJTTNR3Z22UTR2/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":"2026-07-06T19:36:56Z","links":{"resolver":"https://pith.science/pith/U5MS422GV5KCPJTTNR3Z22UTR2","bundle":"https://pith.science/pith/U5MS422GV5KCPJTTNR3Z22UTR2/bundle.json","state":"https://pith.science/pith/U5MS422GV5KCPJTTNR3Z22UTR2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/U5MS422GV5KCPJTTNR3Z22UTR2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:U5MS422GV5KCPJTTNR3Z22UTR2","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":"dc5496529c1ebdf291c22fa8e97a19076f8d03e19754a23837f8acf9897009f0","cross_cats_sorted":["cs.SD","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-03-14T04:26:40Z","title_canon_sha256":"5ca1132542000f0ab641a1fd96938a3a6ab76b38b89d4d027ee7f77f31441737"},"schema_version":"1.0","source":{"id":"2203.06849","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.06849","created_at":"2026-07-05T04:04:56Z"},{"alias_kind":"arxiv_version","alias_value":"2203.06849v1","created_at":"2026-07-05T04:04:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.06849","created_at":"2026-07-05T04:04:56Z"},{"alias_kind":"pith_short_12","alias_value":"U5MS422GV5KC","created_at":"2026-07-05T04:04:56Z"},{"alias_kind":"pith_short_16","alias_value":"U5MS422GV5KCPJTT","created_at":"2026-07-05T04:04:56Z"},{"alias_kind":"pith_short_8","alias_value":"U5MS422G","created_at":"2026-07-05T04:04:56Z"}],"graph_snapshots":[{"event_id":"sha256:dae89d30cf8e15cb617416a778e932d0ee97d71409c0718403492aaccb7aa004","target":"graph","created_at":"2026-07-05T04:04:56Z","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/2203.06849/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Transfer learning has proven to be crucial in advancing the state of speech and natural language processing research in recent years. In speech, a model pre-trained by self-supervised learning transfers remarkably well on multiple tasks. However, the lack of a consistent evaluation methodology is limiting towards a holistic understanding of the efficacy of such models. SUPERB was a step towards introducing a common benchmark to evaluate pre-trained models across various speech tasks. In this paper, we introduce SUPERB-SG, a new benchmark focused on evaluating the semantic and generative capabi","authors_text":"Abdelrahman Mohamed, Andy T. Liu, Cheng-I Jeff Lai, Heng-Jui Chang, Hsiang-Sheng Tsai, Hsuan-Jui Chen, Hung-yi Lee, Jiatong Shi, Kushal Lakhotia, Phil Hall, Shang-Wen Li, Shinji Watanabe, Shu-wen Yang, Shuyan Dong, Wen-Chin Huang, Xuankai Chang, Zili Huang","cross_cats":["cs.SD","eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-03-14T04:26:40Z","title":"SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.06849","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":"sha256:2befc3b044787bdd42b43f1f9990f6e70644fdac569c482e1a7beb0d84d36548","target":"record","created_at":"2026-07-05T04:04:56Z","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":"dc5496529c1ebdf291c22fa8e97a19076f8d03e19754a23837f8acf9897009f0","cross_cats_sorted":["cs.SD","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-03-14T04:26:40Z","title_canon_sha256":"5ca1132542000f0ab641a1fd96938a3a6ab76b38b89d4d027ee7f77f31441737"},"schema_version":"1.0","source":{"id":"2203.06849","kind":"arxiv","version":1}},"canonical_sha256":"a7592e6b46af5427a6736c779d6a938ea25daa626a32777575d2cd186618d900","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a7592e6b46af5427a6736c779d6a938ea25daa626a32777575d2cd186618d900","first_computed_at":"2026-07-05T04:04:56.617472Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:04:56.617472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Kehvbv+wk6V/auV4vB/bJp3RI8c3eoTC5ByUj2JfoXuU94yQPLN1JXgzi17idYCNoWmHI6y67lvdP/wNc0bXCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:04:56.617999Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.06849","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2befc3b044787bdd42b43f1f9990f6e70644fdac569c482e1a7beb0d84d36548","sha256:dae89d30cf8e15cb617416a778e932d0ee97d71409c0718403492aaccb7aa004"],"state_sha256":"49de18cc93517b75722fa3f4160d2dddfe39beffdd27860485572d5506b6ff9c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iyefcn5pJjG4XlonDaySvrWn7zfnR5zoBfiPny+tldn1UTRdEnnal/lS0Ksb5Roy3mDiN5A1/2MgMdlr/ivbCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T19:36:56.152035Z","bundle_sha256":"a8f86be302fb9dfbb6ad668b0e9c6d13ff262acf8c0455b1aeaa044a45b09b14"}}