{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:CCZY4M6A3YFOX6D5HWRZJW75TI","short_pith_number":"pith:CCZY4M6A","canonical_record":{"source":{"id":"2207.00560","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-07-01T17:24:11Z","cross_cats_sorted":[],"title_canon_sha256":"277303dab068a64096da527223bdf7a8367120b85043eaf32b8a550dcfb4acab","abstract_canon_sha256":"79058b520dc0326aa8ca46039c33e7a28c9f2913772709a75239b398483b3332"},"schema_version":"1.0"},"canonical_sha256":"10b38e33c0de0aebf87d3da394dbfd9a2e29e97cb35e699f72585aba84fe3aaa","source":{"kind":"arxiv","id":"2207.00560","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.00560","created_at":"2026-07-05T04:36:44Z"},{"alias_kind":"arxiv_version","alias_value":"2207.00560v1","created_at":"2026-07-05T04:36:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.00560","created_at":"2026-07-05T04:36:44Z"},{"alias_kind":"pith_short_12","alias_value":"CCZY4M6A3YFO","created_at":"2026-07-05T04:36:44Z"},{"alias_kind":"pith_short_16","alias_value":"CCZY4M6A3YFOX6D5","created_at":"2026-07-05T04:36:44Z"},{"alias_kind":"pith_short_8","alias_value":"CCZY4M6A","created_at":"2026-07-05T04:36:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:CCZY4M6A3YFOX6D5HWRZJW75TI","target":"record","payload":{"canonical_record":{"source":{"id":"2207.00560","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-07-01T17:24:11Z","cross_cats_sorted":[],"title_canon_sha256":"277303dab068a64096da527223bdf7a8367120b85043eaf32b8a550dcfb4acab","abstract_canon_sha256":"79058b520dc0326aa8ca46039c33e7a28c9f2913772709a75239b398483b3332"},"schema_version":"1.0"},"canonical_sha256":"10b38e33c0de0aebf87d3da394dbfd9a2e29e97cb35e699f72585aba84fe3aaa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:36:44.499867Z","signature_b64":"trg9jzxfRPbXbJMR42EYKm9bjjbRIANG7GdZdYZZUZNos5sekPy12eR4xMFiEenGf5WH8G24/GXKreiJOLAQBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"10b38e33c0de0aebf87d3da394dbfd9a2e29e97cb35e699f72585aba84fe3aaa","last_reissued_at":"2026-07-05T04:36:44.499435Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:36:44.499435Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.00560","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":"2026-07-05T04:36:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lXY3nqsLvvSZ9VRoYR8aSdP1kbHswsEvIgaBcrOi73l1MxaBfxbn3z93Uh6Q/Kj0p75BNWgoPZVV6Fht7uySAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T14:29:22.995385Z"},"content_sha256":"14c669a30b90bb4108abc4d3a6e3e8d36ca13571c3fa6c861126e546a055fc97","schema_version":"1.0","event_id":"sha256:14c669a30b90bb4108abc4d3a6e3e8d36ca13571c3fa6c861126e546a055fc97"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:CCZY4M6A3YFOX6D5HWRZJW75TI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Is neural language acquisition similar to natural? A chronological probing study","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ekaterina Voloshina, Oleg Serikov, Tatiana Shavrina","submitted_at":"2022-07-01T17:24:11Z","abstract_excerpt":"The probing methodology allows one to obtain a partial representation of linguistic phenomena stored in the inner layers of the neural network, using external classifiers and statistical analysis. Pre-trained transformer-based language models are widely used both for natural language understanding (NLU) and natural language generation (NLG) tasks making them most commonly used for downstream applications. However, little analysis was carried out, whether the models were pre-trained enough or contained knowledge correlated with linguistic theory. We are presenting the chronological probing stud"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.00560","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/2207.00560/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":"2026-07-05T04:36:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DKlSSo2ODmrrilaFCa/XhGD1cLxZbdxEiFNFCsdioza2Em0Pw/cgCqnNbYzztK4GAy+bmSAqGc2ndWMMBDE+Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T14:29:22.995878Z"},"content_sha256":"bb858a3c1904ac4881dd944260aaaed306ca79fa59f5462482b244cc215efb27","schema_version":"1.0","event_id":"sha256:bb858a3c1904ac4881dd944260aaaed306ca79fa59f5462482b244cc215efb27"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CCZY4M6A3YFOX6D5HWRZJW75TI/bundle.json","state_url":"https://pith.science/pith/CCZY4M6A3YFOX6D5HWRZJW75TI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CCZY4M6A3YFOX6D5HWRZJW75TI/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":"2026-08-04T14:29:23Z","links":{"resolver":"https://pith.science/pith/CCZY4M6A3YFOX6D5HWRZJW75TI","bundle":"https://pith.science/pith/CCZY4M6A3YFOX6D5HWRZJW75TI/bundle.json","state":"https://pith.science/pith/CCZY4M6A3YFOX6D5HWRZJW75TI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CCZY4M6A3YFOX6D5HWRZJW75TI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:CCZY4M6A3YFOX6D5HWRZJW75TI","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":"79058b520dc0326aa8ca46039c33e7a28c9f2913772709a75239b398483b3332","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-07-01T17:24:11Z","title_canon_sha256":"277303dab068a64096da527223bdf7a8367120b85043eaf32b8a550dcfb4acab"},"schema_version":"1.0","source":{"id":"2207.00560","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.00560","created_at":"2026-07-05T04:36:44Z"},{"alias_kind":"arxiv_version","alias_value":"2207.00560v1","created_at":"2026-07-05T04:36:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.00560","created_at":"2026-07-05T04:36:44Z"},{"alias_kind":"pith_short_12","alias_value":"CCZY4M6A3YFO","created_at":"2026-07-05T04:36:44Z"},{"alias_kind":"pith_short_16","alias_value":"CCZY4M6A3YFOX6D5","created_at":"2026-07-05T04:36:44Z"},{"alias_kind":"pith_short_8","alias_value":"CCZY4M6A","created_at":"2026-07-05T04:36:44Z"}],"graph_snapshots":[{"event_id":"sha256:bb858a3c1904ac4881dd944260aaaed306ca79fa59f5462482b244cc215efb27","target":"graph","created_at":"2026-07-05T04:36:44Z","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/2207.00560/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The probing methodology allows one to obtain a partial representation of linguistic phenomena stored in the inner layers of the neural network, using external classifiers and statistical analysis. Pre-trained transformer-based language models are widely used both for natural language understanding (NLU) and natural language generation (NLG) tasks making them most commonly used for downstream applications. However, little analysis was carried out, whether the models were pre-trained enough or contained knowledge correlated with linguistic theory. We are presenting the chronological probing stud","authors_text":"Ekaterina Voloshina, Oleg Serikov, Tatiana Shavrina","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-07-01T17:24:11Z","title":"Is neural language acquisition similar to natural? A chronological probing study"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.00560","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":"sha256:14c669a30b90bb4108abc4d3a6e3e8d36ca13571c3fa6c861126e546a055fc97","target":"record","created_at":"2026-07-05T04:36:44Z","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":"79058b520dc0326aa8ca46039c33e7a28c9f2913772709a75239b398483b3332","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-07-01T17:24:11Z","title_canon_sha256":"277303dab068a64096da527223bdf7a8367120b85043eaf32b8a550dcfb4acab"},"schema_version":"1.0","source":{"id":"2207.00560","kind":"arxiv","version":1}},"canonical_sha256":"10b38e33c0de0aebf87d3da394dbfd9a2e29e97cb35e699f72585aba84fe3aaa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"10b38e33c0de0aebf87d3da394dbfd9a2e29e97cb35e699f72585aba84fe3aaa","first_computed_at":"2026-07-05T04:36:44.499435Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:36:44.499435Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"trg9jzxfRPbXbJMR42EYKm9bjjbRIANG7GdZdYZZUZNos5sekPy12eR4xMFiEenGf5WH8G24/GXKreiJOLAQBA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:36:44.499867Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.00560","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:14c669a30b90bb4108abc4d3a6e3e8d36ca13571c3fa6c861126e546a055fc97","sha256:bb858a3c1904ac4881dd944260aaaed306ca79fa59f5462482b244cc215efb27"],"state_sha256":"878b142a46db0c8692f3710e276c5264ff03e9b96db46c369bfe5562e4f024ff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Wi1HEQmfwJVjGBdRBmUuwpAvKubwiF0RfTljB5DNGcL+LvJii+LDYnn01EOpdkADUypcj/1qI5UU1NVAdFyoBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T14:29:23.005827Z","bundle_sha256":"dae0de14d9856677700b372c879fa871d925c0b3ccfb8d71ee2fbe94926186f1"}}