{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:CHNUWEDWDP63SFWWLT2734TDLY","short_pith_number":"pith:CHNUWEDW","canonical_record":{"source":{"id":"2205.12446","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-05-25T02:29:03Z","cross_cats_sorted":["cs.LG","cs.SD","eess.AS"],"title_canon_sha256":"25a37c297c3b2e27efebc4e78d84b48f5d1cdf1541b91c389f3c4abffbf5a85d","abstract_canon_sha256":"221b16bd34b9a6b278b0eb958f4efb7cf4941839525b6e9d0b8a7af26231c811"},"schema_version":"1.0"},"canonical_sha256":"11db4b10761bfdb916d65cf5fdf2635e3704b0b3c4b270e28c3009ed2033c7fe","source":{"kind":"arxiv","id":"2205.12446","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.12446","created_at":"2026-07-05T04:26:25Z"},{"alias_kind":"arxiv_version","alias_value":"2205.12446v1","created_at":"2026-07-05T04:26:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.12446","created_at":"2026-07-05T04:26:25Z"},{"alias_kind":"pith_short_12","alias_value":"CHNUWEDWDP63","created_at":"2026-07-05T04:26:25Z"},{"alias_kind":"pith_short_16","alias_value":"CHNUWEDWDP63SFWW","created_at":"2026-07-05T04:26:25Z"},{"alias_kind":"pith_short_8","alias_value":"CHNUWEDW","created_at":"2026-07-05T04:26:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:CHNUWEDWDP63SFWWLT2734TDLY","target":"record","payload":{"canonical_record":{"source":{"id":"2205.12446","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-05-25T02:29:03Z","cross_cats_sorted":["cs.LG","cs.SD","eess.AS"],"title_canon_sha256":"25a37c297c3b2e27efebc4e78d84b48f5d1cdf1541b91c389f3c4abffbf5a85d","abstract_canon_sha256":"221b16bd34b9a6b278b0eb958f4efb7cf4941839525b6e9d0b8a7af26231c811"},"schema_version":"1.0"},"canonical_sha256":"11db4b10761bfdb916d65cf5fdf2635e3704b0b3c4b270e28c3009ed2033c7fe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:26:25.787675Z","signature_b64":"++QjTgPh5l2RHd778vnGpPGV3MsZIXzoEFDrvtW4EyzWRltyQo5oHkfHg2KC/NRb9zVzqtqD5+4AsKncDWGdCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"11db4b10761bfdb916d65cf5fdf2635e3704b0b3c4b270e28c3009ed2033c7fe","last_reissued_at":"2026-07-05T04:26:25.787252Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:26:25.787252Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.12446","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":"2026-07-05T04:26:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8CAELJw8YslhMe+4z9Ao9YsSpacP3JXVgf43StqVtnJ2ofWy+d8MCCuDS9kU/Dm9TSJbdJm/gnKDY4knf6JGDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T16:16:43.842419Z"},"content_sha256":"e3e74bcb282d3245066130255fbbbff692ed9bc7f56e06e8d34552d5faf7219d","schema_version":"1.0","event_id":"sha256:e3e74bcb282d3245066130255fbbbff692ed9bc7f56e06e8d34552d5faf7219d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:CHNUWEDWDP63SFWWLT2734TDLY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","cs.SD","eess.AS"],"primary_cat":"cs.CL","authors_text":"Alexis Conneau, Ankur Bapna, Clara Rivera, Jason Riesa, Min Ma, Siddharth Dalmia, Simran Khanuja, Vera Axelrod, Yu Zhang","submitted_at":"2022-05-25T02:29:03Z","abstract_excerpt":"We introduce FLEURS, the Few-shot Learning Evaluation of Universal Representations of Speech benchmark. FLEURS is an n-way parallel speech dataset in 102 languages built on top of the machine translation FLoRes-101 benchmark, with approximately 12 hours of speech supervision per language. FLEURS can be used for a variety of speech tasks, including Automatic Speech Recognition (ASR), Speech Language Identification (Speech LangID), Translation and Retrieval. In this paper, we provide baselines for the tasks based on multilingual pre-trained models like mSLAM. The goal of FLEURS is to enable spee"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.12446","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/2205.12446/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":"2026-07-05T04:26:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NAtzet5JRu4zcBmBlxIsysO5qu5EJ5Yuuh5UpPWn1aQgxIkPdl2koKs3rVM/oVI2uZHt2DjzDrwKQgVI5GkKBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T16:16:43.842803Z"},"content_sha256":"a634125ce8b160c4b80eda8c9ac7d697ecae1994090ca025136a00745935a02f","schema_version":"1.0","event_id":"sha256:a634125ce8b160c4b80eda8c9ac7d697ecae1994090ca025136a00745935a02f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CHNUWEDWDP63SFWWLT2734TDLY/bundle.json","state_url":"https://pith.science/pith/CHNUWEDWDP63SFWWLT2734TDLY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CHNUWEDWDP63SFWWLT2734TDLY/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":"2026-08-03T16:16:43Z","links":{"resolver":"https://pith.science/pith/CHNUWEDWDP63SFWWLT2734TDLY","bundle":"https://pith.science/pith/CHNUWEDWDP63SFWWLT2734TDLY/bundle.json","state":"https://pith.science/pith/CHNUWEDWDP63SFWWLT2734TDLY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CHNUWEDWDP63SFWWLT2734TDLY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:CHNUWEDWDP63SFWWLT2734TDLY","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":"221b16bd34b9a6b278b0eb958f4efb7cf4941839525b6e9d0b8a7af26231c811","cross_cats_sorted":["cs.LG","cs.SD","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-05-25T02:29:03Z","title_canon_sha256":"25a37c297c3b2e27efebc4e78d84b48f5d1cdf1541b91c389f3c4abffbf5a85d"},"schema_version":"1.0","source":{"id":"2205.12446","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.12446","created_at":"2026-07-05T04:26:25Z"},{"alias_kind":"arxiv_version","alias_value":"2205.12446v1","created_at":"2026-07-05T04:26:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.12446","created_at":"2026-07-05T04:26:25Z"},{"alias_kind":"pith_short_12","alias_value":"CHNUWEDWDP63","created_at":"2026-07-05T04:26:25Z"},{"alias_kind":"pith_short_16","alias_value":"CHNUWEDWDP63SFWW","created_at":"2026-07-05T04:26:25Z"},{"alias_kind":"pith_short_8","alias_value":"CHNUWEDW","created_at":"2026-07-05T04:26:25Z"}],"graph_snapshots":[{"event_id":"sha256:a634125ce8b160c4b80eda8c9ac7d697ecae1994090ca025136a00745935a02f","target":"graph","created_at":"2026-07-05T04:26:25Z","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/2205.12446/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce FLEURS, the Few-shot Learning Evaluation of Universal Representations of Speech benchmark. FLEURS is an n-way parallel speech dataset in 102 languages built on top of the machine translation FLoRes-101 benchmark, with approximately 12 hours of speech supervision per language. FLEURS can be used for a variety of speech tasks, including Automatic Speech Recognition (ASR), Speech Language Identification (Speech LangID), Translation and Retrieval. In this paper, we provide baselines for the tasks based on multilingual pre-trained models like mSLAM. The goal of FLEURS is to enable spee","authors_text":"Alexis Conneau, Ankur Bapna, Clara Rivera, Jason Riesa, Min Ma, Siddharth Dalmia, Simran Khanuja, Vera Axelrod, Yu Zhang","cross_cats":["cs.LG","cs.SD","eess.AS"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-05-25T02:29:03Z","title":"FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.12446","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:e3e74bcb282d3245066130255fbbbff692ed9bc7f56e06e8d34552d5faf7219d","target":"record","created_at":"2026-07-05T04:26:25Z","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":"221b16bd34b9a6b278b0eb958f4efb7cf4941839525b6e9d0b8a7af26231c811","cross_cats_sorted":["cs.LG","cs.SD","eess.AS"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-05-25T02:29:03Z","title_canon_sha256":"25a37c297c3b2e27efebc4e78d84b48f5d1cdf1541b91c389f3c4abffbf5a85d"},"schema_version":"1.0","source":{"id":"2205.12446","kind":"arxiv","version":1}},"canonical_sha256":"11db4b10761bfdb916d65cf5fdf2635e3704b0b3c4b270e28c3009ed2033c7fe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"11db4b10761bfdb916d65cf5fdf2635e3704b0b3c4b270e28c3009ed2033c7fe","first_computed_at":"2026-07-05T04:26:25.787252Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:26:25.787252Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"++QjTgPh5l2RHd778vnGpPGV3MsZIXzoEFDrvtW4EyzWRltyQo5oHkfHg2KC/NRb9zVzqtqD5+4AsKncDWGdCA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:26:25.787675Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.12446","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e3e74bcb282d3245066130255fbbbff692ed9bc7f56e06e8d34552d5faf7219d","sha256:a634125ce8b160c4b80eda8c9ac7d697ecae1994090ca025136a00745935a02f"],"state_sha256":"2c6c2b770b9f7970a007b2724b5a8b4777adeefa65a0c89e0896982e376561d6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7Eq7fFcT16c+xyWBvq4MwgDkqGC3a8aVkYxVsjZWAi6t5J38q8tIANZjfF1lDOjFJefZYcbLfxG90CSB1LtKAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T16:16:43.845431Z","bundle_sha256":"f358342122d3b55a80a5e42d4cfe5edf44ed12a51a4bdb2a3af39a4e3cb4ffd1"}}