{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:MZ4KFFVCCFF2AKZV47J5WXPY4Z","short_pith_number":"pith:MZ4KFFVC","canonical_record":{"source":{"id":"2104.06644","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-14T06:30:36Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"3854563f4497442422596ae69e563d275f245bce6878acab7299be89eb0836ab","abstract_canon_sha256":"696f12f70de7586ee2702793833475a4f03cad07deaf2b1b8d9d0fa18036d7e2"},"schema_version":"1.0"},"canonical_sha256":"6678a296a2114ba02b35e7d3db5df8e64b273ba754c7c3485f6220b1bf597f17","source":{"kind":"arxiv","id":"2104.06644","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.06644","created_at":"2026-07-05T03:13:02Z"},{"alias_kind":"arxiv_version","alias_value":"2104.06644v2","created_at":"2026-07-05T03:13:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.06644","created_at":"2026-07-05T03:13:02Z"},{"alias_kind":"pith_short_12","alias_value":"MZ4KFFVCCFF2","created_at":"2026-07-05T03:13:02Z"},{"alias_kind":"pith_short_16","alias_value":"MZ4KFFVCCFF2AKZV","created_at":"2026-07-05T03:13:02Z"},{"alias_kind":"pith_short_8","alias_value":"MZ4KFFVC","created_at":"2026-07-05T03:13:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:MZ4KFFVCCFF2AKZV47J5WXPY4Z","target":"record","payload":{"canonical_record":{"source":{"id":"2104.06644","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-14T06:30:36Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"3854563f4497442422596ae69e563d275f245bce6878acab7299be89eb0836ab","abstract_canon_sha256":"696f12f70de7586ee2702793833475a4f03cad07deaf2b1b8d9d0fa18036d7e2"},"schema_version":"1.0"},"canonical_sha256":"6678a296a2114ba02b35e7d3db5df8e64b273ba754c7c3485f6220b1bf597f17","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:13:02.879268Z","signature_b64":"GrnUn9Ib+oJRNf/EeeGn1uNG62S0tzrYVXAz7zRu8XUvhHv3ipbPRD/2TyszFBAfPGggvlc5rtsuXxq7z0XuDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6678a296a2114ba02b35e7d3db5df8e64b273ba754c7c3485f6220b1bf597f17","last_reissued_at":"2026-07-05T03:13:02.878798Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:13:02.878798Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.06644","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:13:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"msyqojgEZI44jhAU+Gp3TWkTE4WaABOhpMImQwy0Me+6DA3K4T6ZqQVfr3SyLCMv6VknUyyatff2nHfNsFFWBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T02:16:37.823217Z"},"content_sha256":"ef2f3411ec2ed747432f8273a727ffc93fee8c2b9134405d6ce85f3396f4e2e0","schema_version":"1.0","event_id":"sha256:ef2f3411ec2ed747432f8273a727ffc93fee8c2b9134405d6ce85f3396f4e2e0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:MZ4KFFVCCFF2AKZV47J5WXPY4Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Adina Williams, Dieuwke Hupkes, Douwe Kiela, Joelle Pineau, Koustuv Sinha, Robin Jia","submitted_at":"2021-04-14T06:30:36Z","abstract_excerpt":"A possible explanation for the impressive performance of masked language model (MLM) pre-training is that such models have learned to represent the syntactic structures prevalent in classical NLP pipelines. In this paper, we propose a different explanation: MLMs succeed on downstream tasks almost entirely due to their ability to model higher-order word co-occurrence statistics. To demonstrate this, we pre-train MLMs on sentences with randomly shuffled word order, and show that these models still achieve high accuracy after fine-tuning on many downstream tasks -- including on tasks specifically"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.06644","kind":"arxiv","version":2},"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/2104.06644/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":"2026-07-05T03:13:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h10X15C1G1oxDbk5C2epPM6W7y+Cv7XIfudMsv+LEn9gs5qnRFA5j7HJ9nhL6+R3XGJoB72qP/Bz2CQp22G0DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T02:16:37.823730Z"},"content_sha256":"b0b43b7033f08339d11d97b2bff40fda9e59affd685544946696993e3bfc4dbc","schema_version":"1.0","event_id":"sha256:b0b43b7033f08339d11d97b2bff40fda9e59affd685544946696993e3bfc4dbc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MZ4KFFVCCFF2AKZV47J5WXPY4Z/bundle.json","state_url":"https://pith.science/pith/MZ4KFFVCCFF2AKZV47J5WXPY4Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MZ4KFFVCCFF2AKZV47J5WXPY4Z/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":"2026-08-09T02:16:37Z","links":{"resolver":"https://pith.science/pith/MZ4KFFVCCFF2AKZV47J5WXPY4Z","bundle":"https://pith.science/pith/MZ4KFFVCCFF2AKZV47J5WXPY4Z/bundle.json","state":"https://pith.science/pith/MZ4KFFVCCFF2AKZV47J5WXPY4Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MZ4KFFVCCFF2AKZV47J5WXPY4Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:MZ4KFFVCCFF2AKZV47J5WXPY4Z","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":"696f12f70de7586ee2702793833475a4f03cad07deaf2b1b8d9d0fa18036d7e2","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-14T06:30:36Z","title_canon_sha256":"3854563f4497442422596ae69e563d275f245bce6878acab7299be89eb0836ab"},"schema_version":"1.0","source":{"id":"2104.06644","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.06644","created_at":"2026-07-05T03:13:02Z"},{"alias_kind":"arxiv_version","alias_value":"2104.06644v2","created_at":"2026-07-05T03:13:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.06644","created_at":"2026-07-05T03:13:02Z"},{"alias_kind":"pith_short_12","alias_value":"MZ4KFFVCCFF2","created_at":"2026-07-05T03:13:02Z"},{"alias_kind":"pith_short_16","alias_value":"MZ4KFFVCCFF2AKZV","created_at":"2026-07-05T03:13:02Z"},{"alias_kind":"pith_short_8","alias_value":"MZ4KFFVC","created_at":"2026-07-05T03:13:02Z"}],"graph_snapshots":[{"event_id":"sha256:b0b43b7033f08339d11d97b2bff40fda9e59affd685544946696993e3bfc4dbc","target":"graph","created_at":"2026-07-05T03:13:02Z","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/2104.06644/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A possible explanation for the impressive performance of masked language model (MLM) pre-training is that such models have learned to represent the syntactic structures prevalent in classical NLP pipelines. In this paper, we propose a different explanation: MLMs succeed on downstream tasks almost entirely due to their ability to model higher-order word co-occurrence statistics. To demonstrate this, we pre-train MLMs on sentences with randomly shuffled word order, and show that these models still achieve high accuracy after fine-tuning on many downstream tasks -- including on tasks specifically","authors_text":"Adina Williams, Dieuwke Hupkes, Douwe Kiela, Joelle Pineau, Koustuv Sinha, Robin Jia","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-14T06:30:36Z","title":"Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.06644","kind":"arxiv","version":2},"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:ef2f3411ec2ed747432f8273a727ffc93fee8c2b9134405d6ce85f3396f4e2e0","target":"record","created_at":"2026-07-05T03:13:02Z","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":"696f12f70de7586ee2702793833475a4f03cad07deaf2b1b8d9d0fa18036d7e2","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-14T06:30:36Z","title_canon_sha256":"3854563f4497442422596ae69e563d275f245bce6878acab7299be89eb0836ab"},"schema_version":"1.0","source":{"id":"2104.06644","kind":"arxiv","version":2}},"canonical_sha256":"6678a296a2114ba02b35e7d3db5df8e64b273ba754c7c3485f6220b1bf597f17","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6678a296a2114ba02b35e7d3db5df8e64b273ba754c7c3485f6220b1bf597f17","first_computed_at":"2026-07-05T03:13:02.878798Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:13:02.878798Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GrnUn9Ib+oJRNf/EeeGn1uNG62S0tzrYVXAz7zRu8XUvhHv3ipbPRD/2TyszFBAfPGggvlc5rtsuXxq7z0XuDw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:13:02.879268Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.06644","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ef2f3411ec2ed747432f8273a727ffc93fee8c2b9134405d6ce85f3396f4e2e0","sha256:b0b43b7033f08339d11d97b2bff40fda9e59affd685544946696993e3bfc4dbc"],"state_sha256":"6663552395cf44ade9fab6f2520caa01871891e0d427ade3b0a0a96133625145"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NFoKDIppHtVZjGrTVYtjopTY7H8gjR2umZ1fbVf2YQnlqirqVFz0oS949+n7W8aK7TvQsbxJ9+g19EkPCYAGDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T02:16:37.827790Z","bundle_sha256":"4d0ea6ca536aebc4e1171c8201050d8c22d6237032a85fc6198b2c116e2d9f74"}}