{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:JIAAYLZBDSKXAPF5WVF5NHYLPV","short_pith_number":"pith:JIAAYLZB","canonical_record":{"source":{"id":"2010.14042","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-27T04:03:47Z","cross_cats_sorted":[],"title_canon_sha256":"2f694829ccfc08478e99570b37c98640398467ece329b7d800afbe7f0185712d","abstract_canon_sha256":"4fc054dab133a119b65d5680b02122e67495b424d18f72bf26f5d4378f4ff909"},"schema_version":"1.0"},"canonical_sha256":"4a000c2f211c95703cbdb54bd69f0b7d5d35d4b17249946f00e752fcb14f7552","source":{"kind":"arxiv","id":"2010.14042","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.14042","created_at":"2026-07-05T01:46:30Z"},{"alias_kind":"arxiv_version","alias_value":"2010.14042v1","created_at":"2026-07-05T01:46:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.14042","created_at":"2026-07-05T01:46:30Z"},{"alias_kind":"pith_short_12","alias_value":"JIAAYLZBDSKX","created_at":"2026-07-05T01:46:30Z"},{"alias_kind":"pith_short_16","alias_value":"JIAAYLZBDSKXAPF5","created_at":"2026-07-05T01:46:30Z"},{"alias_kind":"pith_short_8","alias_value":"JIAAYLZB","created_at":"2026-07-05T01:46:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:JIAAYLZBDSKXAPF5WVF5NHYLPV","target":"record","payload":{"canonical_record":{"source":{"id":"2010.14042","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-27T04:03:47Z","cross_cats_sorted":[],"title_canon_sha256":"2f694829ccfc08478e99570b37c98640398467ece329b7d800afbe7f0185712d","abstract_canon_sha256":"4fc054dab133a119b65d5680b02122e67495b424d18f72bf26f5d4378f4ff909"},"schema_version":"1.0"},"canonical_sha256":"4a000c2f211c95703cbdb54bd69f0b7d5d35d4b17249946f00e752fcb14f7552","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:46:30.752295Z","signature_b64":"w4KA1Ly8nWWalTW/NH60MDXZmTOwpT5ytMuEhaKqLQco4+QejdT7oVKB8M83BzXOongvnlB1//VQJYtMjR/rDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4a000c2f211c95703cbdb54bd69f0b7d5d35d4b17249946f00e752fcb14f7552","last_reissued_at":"2026-07-05T01:46:30.751846Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:46:30.751846Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.14042","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":"2026-07-05T01:46:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OQEqHnqAvOxsH6C/UWedE+aVCY4VrEI0sIXA9u6rj2l9kYCyoPzCDIaQCXO3xX+LdQTBN3ESPThmaXQRX1aEBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:41:45.962103Z"},"content_sha256":"b795a9743f6b38e7e5ad28e1f079e95c1ba314e54e495632ef8031d87fb96b01","schema_version":"1.0","event_id":"sha256:b795a9743f6b38e7e5ad28e1f079e95c1ba314e54e495632ef8031d87fb96b01"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:JIAAYLZBDSKXAPF5WVF5NHYLPV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"To BERT or Not to BERT: Comparing Task-specific and Task-agnostic Semi-Supervised Approaches for Sequence Tagging","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Faisal Ladhak, Jie Ma, Kasturi Bhattacharjee, Miguel Ballesteros, Rishita Anubhai, Smaranda Muresan, Yaser Al-Onaizan","submitted_at":"2020-10-27T04:03:47Z","abstract_excerpt":"Leveraging large amounts of unlabeled data using Transformer-like architectures, like BERT, has gained popularity in recent times owing to their effectiveness in learning general representations that can then be further fine-tuned for downstream tasks to much success. However, training these models can be costly both from an economic and environmental standpoint. In this work, we investigate how to effectively use unlabeled data: by exploring the task-specific semi-supervised approach, Cross-View Training (CVT) and comparing it with task-agnostic BERT in multiple settings that include domain a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.14042","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/2010.14042/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":"2026-07-05T01:46:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Gh+kzKlJWD0AYNI90GHO0jW1IGEQLgJoeRy4cFKRnWlz7+pG70b0n+3s08EBKy0yINNULVHXniU+HLnFBav+Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:41:45.962886Z"},"content_sha256":"31e99b27633c7c998eb0b21e87db956d39dff32b7e2b45a0074ef7f86eacafa2","schema_version":"1.0","event_id":"sha256:31e99b27633c7c998eb0b21e87db956d39dff32b7e2b45a0074ef7f86eacafa2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JIAAYLZBDSKXAPF5WVF5NHYLPV/bundle.json","state_url":"https://pith.science/pith/JIAAYLZBDSKXAPF5WVF5NHYLPV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JIAAYLZBDSKXAPF5WVF5NHYLPV/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":"2026-07-05T15:41:45Z","links":{"resolver":"https://pith.science/pith/JIAAYLZBDSKXAPF5WVF5NHYLPV","bundle":"https://pith.science/pith/JIAAYLZBDSKXAPF5WVF5NHYLPV/bundle.json","state":"https://pith.science/pith/JIAAYLZBDSKXAPF5WVF5NHYLPV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JIAAYLZBDSKXAPF5WVF5NHYLPV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:JIAAYLZBDSKXAPF5WVF5NHYLPV","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":"4fc054dab133a119b65d5680b02122e67495b424d18f72bf26f5d4378f4ff909","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-27T04:03:47Z","title_canon_sha256":"2f694829ccfc08478e99570b37c98640398467ece329b7d800afbe7f0185712d"},"schema_version":"1.0","source":{"id":"2010.14042","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.14042","created_at":"2026-07-05T01:46:30Z"},{"alias_kind":"arxiv_version","alias_value":"2010.14042v1","created_at":"2026-07-05T01:46:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.14042","created_at":"2026-07-05T01:46:30Z"},{"alias_kind":"pith_short_12","alias_value":"JIAAYLZBDSKX","created_at":"2026-07-05T01:46:30Z"},{"alias_kind":"pith_short_16","alias_value":"JIAAYLZBDSKXAPF5","created_at":"2026-07-05T01:46:30Z"},{"alias_kind":"pith_short_8","alias_value":"JIAAYLZB","created_at":"2026-07-05T01:46:30Z"}],"graph_snapshots":[{"event_id":"sha256:31e99b27633c7c998eb0b21e87db956d39dff32b7e2b45a0074ef7f86eacafa2","target":"graph","created_at":"2026-07-05T01:46:30Z","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/2010.14042/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Leveraging large amounts of unlabeled data using Transformer-like architectures, like BERT, has gained popularity in recent times owing to their effectiveness in learning general representations that can then be further fine-tuned for downstream tasks to much success. However, training these models can be costly both from an economic and environmental standpoint. In this work, we investigate how to effectively use unlabeled data: by exploring the task-specific semi-supervised approach, Cross-View Training (CVT) and comparing it with task-agnostic BERT in multiple settings that include domain a","authors_text":"Faisal Ladhak, Jie Ma, Kasturi Bhattacharjee, Miguel Ballesteros, Rishita Anubhai, Smaranda Muresan, Yaser Al-Onaizan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-27T04:03:47Z","title":"To BERT or Not to BERT: Comparing Task-specific and Task-agnostic Semi-Supervised Approaches for Sequence Tagging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.14042","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:b795a9743f6b38e7e5ad28e1f079e95c1ba314e54e495632ef8031d87fb96b01","target":"record","created_at":"2026-07-05T01:46:30Z","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":"4fc054dab133a119b65d5680b02122e67495b424d18f72bf26f5d4378f4ff909","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-27T04:03:47Z","title_canon_sha256":"2f694829ccfc08478e99570b37c98640398467ece329b7d800afbe7f0185712d"},"schema_version":"1.0","source":{"id":"2010.14042","kind":"arxiv","version":1}},"canonical_sha256":"4a000c2f211c95703cbdb54bd69f0b7d5d35d4b17249946f00e752fcb14f7552","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4a000c2f211c95703cbdb54bd69f0b7d5d35d4b17249946f00e752fcb14f7552","first_computed_at":"2026-07-05T01:46:30.751846Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:46:30.751846Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"w4KA1Ly8nWWalTW/NH60MDXZmTOwpT5ytMuEhaKqLQco4+QejdT7oVKB8M83BzXOongvnlB1//VQJYtMjR/rDg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:46:30.752295Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.14042","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b795a9743f6b38e7e5ad28e1f079e95c1ba314e54e495632ef8031d87fb96b01","sha256:31e99b27633c7c998eb0b21e87db956d39dff32b7e2b45a0074ef7f86eacafa2"],"state_sha256":"c74ae0c8e109fd06bd8fc8dfbacc09289afb957f120f34aa115d2db9945b7f02"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LquRcgsHvCzzwU4frfl1p5OzwDbq3XWFNKAyAdOlXFnpqQARXZya4PKtwXl0VRAGG3fqxnioX+7JiBOxputACw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T15:41:45.966163Z","bundle_sha256":"e01c3dda0a755916712c055e047689ac1c43dfed36ef8c8e2065a578bb7b0de0"}}