{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:XTYH5XQ6QT5NRI7HROW6I3ZPIB","short_pith_number":"pith:XTYH5XQ6","canonical_record":{"source":{"id":"1907.10529","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-24T15:43:40Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"4d75ee6c126219ddd6ada0ecb0ef65552be36a6b225977e05b13324bf6a76cc7","abstract_canon_sha256":"2484c3d563d6d1a0bbbd1032759473e973d9263f1de09c7475e5776e6d1e3e62"},"schema_version":"1.0"},"canonical_sha256":"bcf07ede1e84fad8a3e78bade46f2f4055e1e824a6ff49fc31d58d9c8bdb8dd7","source":{"kind":"arxiv","id":"1907.10529","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.10529","created_at":"2026-07-05T00:34:16Z"},{"alias_kind":"arxiv_version","alias_value":"1907.10529v3","created_at":"2026-07-05T00:34:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.10529","created_at":"2026-07-05T00:34:16Z"},{"alias_kind":"pith_short_12","alias_value":"XTYH5XQ6QT5N","created_at":"2026-07-05T00:34:16Z"},{"alias_kind":"pith_short_16","alias_value":"XTYH5XQ6QT5NRI7H","created_at":"2026-07-05T00:34:16Z"},{"alias_kind":"pith_short_8","alias_value":"XTYH5XQ6","created_at":"2026-07-05T00:34:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:XTYH5XQ6QT5NRI7HROW6I3ZPIB","target":"record","payload":{"canonical_record":{"source":{"id":"1907.10529","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-24T15:43:40Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"4d75ee6c126219ddd6ada0ecb0ef65552be36a6b225977e05b13324bf6a76cc7","abstract_canon_sha256":"2484c3d563d6d1a0bbbd1032759473e973d9263f1de09c7475e5776e6d1e3e62"},"schema_version":"1.0"},"canonical_sha256":"bcf07ede1e84fad8a3e78bade46f2f4055e1e824a6ff49fc31d58d9c8bdb8dd7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:34:16.421971Z","signature_b64":"zgFZEXQDRvN0nTEgBDXxdvKUk1hkT9sXbRQdB3ocI5Qlqc5ehaue123hcBXE+WVJX6V4TfsztYgum1DAimwuDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bcf07ede1e84fad8a3e78bade46f2f4055e1e824a6ff49fc31d58d9c8bdb8dd7","last_reissued_at":"2026-07-05T00:34:16.421471Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:34:16.421471Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.10529","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:34:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p7gHwmvruzo1i5l8ObK6fJi9rGt7CMdJFa+d4DkRbi1utHg4ACV4q6nYVX0N7ftLtQSIi2+nvEh4Q2SoI6uXBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T13:36:16.371164Z"},"content_sha256":"a61b1e8f68b6bbca90896bd1196636bbc5a52bbe134b0ca424cf47b59e171443","schema_version":"1.0","event_id":"sha256:a61b1e8f68b6bbca90896bd1196636bbc5a52bbe134b0ca424cf47b59e171443"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:XTYH5XQ6QT5NRI7HROW6I3ZPIB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SpanBERT: Improving Pre-training by Representing and Predicting Spans","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Daniel S. Weld, Danqi Chen, Luke Zettlemoyer, Mandar Joshi, Omer Levy, Yinhan Liu","submitted_at":"2019-07-24T15:43:40Z","abstract_excerpt":"We present SpanBERT, a pre-training method that is designed to better represent and predict spans of text. Our approach extends BERT by (1) masking contiguous random spans, rather than random tokens, and (2) training the span boundary representations to predict the entire content of the masked span, without relying on the individual token representations within it. SpanBERT consistently outperforms BERT and our better-tuned baselines, with substantial gains on span selection tasks such as question answering and coreference resolution. In particular, with the same training data and model size a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.10529","kind":"arxiv","version":3},"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/1907.10529/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":"2026-07-05T00:34:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YmmCKie0GvF43+jj1eh4lljd5HeJatbt73A6Z/c2h7EpGQXN0yW35PNRmwKpCj8kqxP9LtWO4X73A9BmoxlTCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T13:36:16.371705Z"},"content_sha256":"e3d88d278ed4408d8625aeab977dcaa57fda5156c0388d80638710b2a787596d","schema_version":"1.0","event_id":"sha256:e3d88d278ed4408d8625aeab977dcaa57fda5156c0388d80638710b2a787596d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XTYH5XQ6QT5NRI7HROW6I3ZPIB/bundle.json","state_url":"https://pith.science/pith/XTYH5XQ6QT5NRI7HROW6I3ZPIB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XTYH5XQ6QT5NRI7HROW6I3ZPIB/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":"2026-07-31T13:36:16Z","links":{"resolver":"https://pith.science/pith/XTYH5XQ6QT5NRI7HROW6I3ZPIB","bundle":"https://pith.science/pith/XTYH5XQ6QT5NRI7HROW6I3ZPIB/bundle.json","state":"https://pith.science/pith/XTYH5XQ6QT5NRI7HROW6I3ZPIB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XTYH5XQ6QT5NRI7HROW6I3ZPIB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:XTYH5XQ6QT5NRI7HROW6I3ZPIB","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":"2484c3d563d6d1a0bbbd1032759473e973d9263f1de09c7475e5776e6d1e3e62","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-24T15:43:40Z","title_canon_sha256":"4d75ee6c126219ddd6ada0ecb0ef65552be36a6b225977e05b13324bf6a76cc7"},"schema_version":"1.0","source":{"id":"1907.10529","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.10529","created_at":"2026-07-05T00:34:16Z"},{"alias_kind":"arxiv_version","alias_value":"1907.10529v3","created_at":"2026-07-05T00:34:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.10529","created_at":"2026-07-05T00:34:16Z"},{"alias_kind":"pith_short_12","alias_value":"XTYH5XQ6QT5N","created_at":"2026-07-05T00:34:16Z"},{"alias_kind":"pith_short_16","alias_value":"XTYH5XQ6QT5NRI7H","created_at":"2026-07-05T00:34:16Z"},{"alias_kind":"pith_short_8","alias_value":"XTYH5XQ6","created_at":"2026-07-05T00:34:16Z"}],"graph_snapshots":[{"event_id":"sha256:e3d88d278ed4408d8625aeab977dcaa57fda5156c0388d80638710b2a787596d","target":"graph","created_at":"2026-07-05T00:34:16Z","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/1907.10529/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present SpanBERT, a pre-training method that is designed to better represent and predict spans of text. Our approach extends BERT by (1) masking contiguous random spans, rather than random tokens, and (2) training the span boundary representations to predict the entire content of the masked span, without relying on the individual token representations within it. SpanBERT consistently outperforms BERT and our better-tuned baselines, with substantial gains on span selection tasks such as question answering and coreference resolution. In particular, with the same training data and model size a","authors_text":"Daniel S. Weld, Danqi Chen, Luke Zettlemoyer, Mandar Joshi, Omer Levy, Yinhan Liu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-24T15:43:40Z","title":"SpanBERT: Improving Pre-training by Representing and Predicting Spans"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.10529","kind":"arxiv","version":3},"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:a61b1e8f68b6bbca90896bd1196636bbc5a52bbe134b0ca424cf47b59e171443","target":"record","created_at":"2026-07-05T00:34:16Z","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":"2484c3d563d6d1a0bbbd1032759473e973d9263f1de09c7475e5776e6d1e3e62","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-07-24T15:43:40Z","title_canon_sha256":"4d75ee6c126219ddd6ada0ecb0ef65552be36a6b225977e05b13324bf6a76cc7"},"schema_version":"1.0","source":{"id":"1907.10529","kind":"arxiv","version":3}},"canonical_sha256":"bcf07ede1e84fad8a3e78bade46f2f4055e1e824a6ff49fc31d58d9c8bdb8dd7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bcf07ede1e84fad8a3e78bade46f2f4055e1e824a6ff49fc31d58d9c8bdb8dd7","first_computed_at":"2026-07-05T00:34:16.421471Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:34:16.421471Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zgFZEXQDRvN0nTEgBDXxdvKUk1hkT9sXbRQdB3ocI5Qlqc5ehaue123hcBXE+WVJX6V4TfsztYgum1DAimwuDA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:34:16.421971Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.10529","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a61b1e8f68b6bbca90896bd1196636bbc5a52bbe134b0ca424cf47b59e171443","sha256:e3d88d278ed4408d8625aeab977dcaa57fda5156c0388d80638710b2a787596d"],"state_sha256":"cb729e20f47dc31806a15e884c2086cb0596d10c27ce2c6591fc2a3e94f5118e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CPeFiShWhnpNt+poq5P+ndf1B2LscmhyooKW1TvNw+4SoKtLDB46l2jy5X5RFAiQRPIefAtZ/nzpWdb6pk+IBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T13:36:16.377202Z","bundle_sha256":"60c4bf14e1382bfdaf4a65b8decef52ed813449da59780c26baf40832e61ed25"}}