{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:JYDEID6SCZF4Y26Z5UO52A4SA3","short_pith_number":"pith:JYDEID6S","schema_version":"1.0","canonical_sha256":"4e06440fd2164bcc6bd9ed1ddd039206d8fc9d548ca116719adfd508177b7002","source":{"kind":"arxiv","id":"1608.02214","version":2},"attestation_state":"computed","paper":{"title":"Robsut Wrod Reocginiton via semi-Character Recurrent Neural Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Benjamin Van Durme, Keisuke Sakaguchi, Kevin Duh, Matt Post","submitted_at":"2016-08-07T13:28:46Z","abstract_excerpt":"Language processing mechanism by humans is generally more robust than computers. The Cmabrigde Uinervtisy (Cambridge University) effect from the psycholinguistics literature has demonstrated such a robust word processing mechanism, where jumbled words (e.g. Cmabrigde / Cambridge) are recognized with little cost. On the other hand, computational models for word recognition (e.g. spelling checkers) perform poorly on data with such noise. Inspired by the findings from the Cmabrigde Uinervtisy effect, we propose a word recognition model based on a semi-character level recurrent neural network (scR"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1608.02214","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-08-07T13:28:46Z","cross_cats_sorted":[],"title_canon_sha256":"ea263c182fa15ab2cab6b16a3e33d8f864598d563f8da7630092e9d7d6ffe3bd","abstract_canon_sha256":"b0d121d367aeeac505e01998e6dee2f0c5d26d0ad0d236878743d4eb46d6d39d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:51:16.694668Z","signature_b64":"9Gxu2J+yYLc+VZ4abKGwiGs2rQeFUSyjfkHogDQ11HZ+n+D+3X1Nz90/QnBcP0hjROhWtMDJ7b7MTnBgGeEDCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4e06440fd2164bcc6bd9ed1ddd039206d8fc9d548ca116719adfd508177b7002","last_reissued_at":"2026-05-18T00:51:16.694151Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:51:16.694151Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Robsut Wrod Reocginiton via semi-Character Recurrent Neural Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Benjamin Van Durme, Keisuke Sakaguchi, Kevin Duh, Matt Post","submitted_at":"2016-08-07T13:28:46Z","abstract_excerpt":"Language processing mechanism by humans is generally more robust than computers. The Cmabrigde Uinervtisy (Cambridge University) effect from the psycholinguistics literature has demonstrated such a robust word processing mechanism, where jumbled words (e.g. Cmabrigde / Cambridge) are recognized with little cost. On the other hand, computational models for word recognition (e.g. spelling checkers) perform poorly on data with such noise. Inspired by the findings from the Cmabrigde Uinervtisy effect, we propose a word recognition model based on a semi-character level recurrent neural network (scR"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.02214","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":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1608.02214","created_at":"2026-05-18T00:51:16.694229+00:00"},{"alias_kind":"arxiv_version","alias_value":"1608.02214v2","created_at":"2026-05-18T00:51:16.694229+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.02214","created_at":"2026-05-18T00:51:16.694229+00:00"},{"alias_kind":"pith_short_12","alias_value":"JYDEID6SCZF4","created_at":"2026-05-18T12:30:25.849896+00:00"},{"alias_kind":"pith_short_16","alias_value":"JYDEID6SCZF4Y26Z","created_at":"2026-05-18T12:30:25.849896+00:00"},{"alias_kind":"pith_short_8","alias_value":"JYDEID6S","created_at":"2026-05-18T12:30:25.849896+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/JYDEID6SCZF4Y26Z5UO52A4SA3","json":"https://pith.science/pith/JYDEID6SCZF4Y26Z5UO52A4SA3.json","graph_json":"https://pith.science/api/pith-number/JYDEID6SCZF4Y26Z5UO52A4SA3/graph.json","events_json":"https://pith.science/api/pith-number/JYDEID6SCZF4Y26Z5UO52A4SA3/events.json","paper":"https://pith.science/paper/JYDEID6S"},"agent_actions":{"view_html":"https://pith.science/pith/JYDEID6SCZF4Y26Z5UO52A4SA3","download_json":"https://pith.science/pith/JYDEID6SCZF4Y26Z5UO52A4SA3.json","view_paper":"https://pith.science/paper/JYDEID6S","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1608.02214&json=true","fetch_graph":"https://pith.science/api/pith-number/JYDEID6SCZF4Y26Z5UO52A4SA3/graph.json","fetch_events":"https://pith.science/api/pith-number/JYDEID6SCZF4Y26Z5UO52A4SA3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JYDEID6SCZF4Y26Z5UO52A4SA3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JYDEID6SCZF4Y26Z5UO52A4SA3/action/storage_attestation","attest_author":"https://pith.science/pith/JYDEID6SCZF4Y26Z5UO52A4SA3/action/author_attestation","sign_citation":"https://pith.science/pith/JYDEID6SCZF4Y26Z5UO52A4SA3/action/citation_signature","submit_replication":"https://pith.science/pith/JYDEID6SCZF4Y26Z5UO52A4SA3/action/replication_record"}},"created_at":"2026-05-18T00:51:16.694229+00:00","updated_at":"2026-05-18T00:51:16.694229+00:00"}