{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:FFD5F2O4B55MAD6CYFBFZ35LJH","short_pith_number":"pith:FFD5F2O4","schema_version":"1.0","canonical_sha256":"2947d2e9dc0f7ac00fc2c1425cefab49c4df67cc9be552b2c44a74954e06181c","source":{"kind":"arxiv","id":"2205.04602","version":2},"attestation_state":"computed","paper":{"title":"A Unified Model for Reverse Dictionary and Definition Modelling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CL","authors_text":"Pinzhen Chen, Zheng Zhao","submitted_at":"2022-05-09T23:52:39Z","abstract_excerpt":"We build a dual-way neural dictionary to retrieve words given definitions, and produce definitions for queried words. The model learns the two tasks simultaneously and handles unknown words via embeddings. It casts a word or a definition to the same representation space through a shared layer, then generates the other form in a multi-task fashion. Our method achieves promising automatic scores on previous benchmarks without extra resources. Human annotators prefer the model's outputs in both reference-less and reference-based evaluation, indicating its practicality. Analysis suggests that mult"},"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":"2205.04602","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-09T23:52:39Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"bc4449363e0f9183a20494630cdd7fd0fe8321821dbc6e7448c2a69cbf2f4b04","abstract_canon_sha256":"40ee138cd4434065751b95565256ce1ecfd037ae1ca707598da8a53063316b85"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:05:05.251126Z","signature_b64":"EifpV6SsSbbBZAxyHxmLPuYudITP0Nlm4gsN6F+wvS6G2gRxOmOg4Uj/Z64uZPGxZnxA7AznBc066PmZ4LIXDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2947d2e9dc0f7ac00fc2c1425cefab49c4df67cc9be552b2c44a74954e06181c","last_reissued_at":"2026-07-05T05:05:05.250703Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:05:05.250703Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Unified Model for Reverse Dictionary and Definition Modelling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CL","authors_text":"Pinzhen Chen, Zheng Zhao","submitted_at":"2022-05-09T23:52:39Z","abstract_excerpt":"We build a dual-way neural dictionary to retrieve words given definitions, and produce definitions for queried words. The model learns the two tasks simultaneously and handles unknown words via embeddings. It casts a word or a definition to the same representation space through a shared layer, then generates the other form in a multi-task fashion. Our method achieves promising automatic scores on previous benchmarks without extra resources. Human annotators prefer the model's outputs in both reference-less and reference-based evaluation, indicating its practicality. Analysis suggests that mult"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.04602","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/2205.04602/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2205.04602","created_at":"2026-07-05T05:05:05.250761+00:00"},{"alias_kind":"arxiv_version","alias_value":"2205.04602v2","created_at":"2026-07-05T05:05:05.250761+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.04602","created_at":"2026-07-05T05:05:05.250761+00:00"},{"alias_kind":"pith_short_12","alias_value":"FFD5F2O4B55M","created_at":"2026-07-05T05:05:05.250761+00:00"},{"alias_kind":"pith_short_16","alias_value":"FFD5F2O4B55MAD6C","created_at":"2026-07-05T05:05:05.250761+00:00"},{"alias_kind":"pith_short_8","alias_value":"FFD5F2O4","created_at":"2026-07-05T05:05:05.250761+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2412.06654","citing_title":"GEAR: A Simple GENERATE, EMBED, AVERAGE AND RANK Approach for Unsupervised Reverse Dictionary","ref_index":14,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/FFD5F2O4B55MAD6CYFBFZ35LJH","json":"https://pith.science/pith/FFD5F2O4B55MAD6CYFBFZ35LJH.json","graph_json":"https://pith.science/api/pith-number/FFD5F2O4B55MAD6CYFBFZ35LJH/graph.json","events_json":"https://pith.science/api/pith-number/FFD5F2O4B55MAD6CYFBFZ35LJH/events.json","paper":"https://pith.science/paper/FFD5F2O4"},"agent_actions":{"view_html":"https://pith.science/pith/FFD5F2O4B55MAD6CYFBFZ35LJH","download_json":"https://pith.science/pith/FFD5F2O4B55MAD6CYFBFZ35LJH.json","view_paper":"https://pith.science/paper/FFD5F2O4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2205.04602&json=true","fetch_graph":"https://pith.science/api/pith-number/FFD5F2O4B55MAD6CYFBFZ35LJH/graph.json","fetch_events":"https://pith.science/api/pith-number/FFD5F2O4B55MAD6CYFBFZ35LJH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FFD5F2O4B55MAD6CYFBFZ35LJH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FFD5F2O4B55MAD6CYFBFZ35LJH/action/storage_attestation","attest_author":"https://pith.science/pith/FFD5F2O4B55MAD6CYFBFZ35LJH/action/author_attestation","sign_citation":"https://pith.science/pith/FFD5F2O4B55MAD6CYFBFZ35LJH/action/citation_signature","submit_replication":"https://pith.science/pith/FFD5F2O4B55MAD6CYFBFZ35LJH/action/replication_record"}},"created_at":"2026-07-05T05:05:05.250761+00:00","updated_at":"2026-07-05T05:05:05.250761+00:00"}