{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:SVYUBFFSLACE5KKY6E65LZ5UYK","short_pith_number":"pith:SVYUBFFS","schema_version":"1.0","canonical_sha256":"95714094b258044ea958f13dd5e7b4c29e2abfbcae0b164f4d445cc312b1f595","source":{"kind":"arxiv","id":"1804.08139","version":1},"attestation_state":"computed","paper":{"title":"Same Representation, Different Attentions: Shareable Sentence Representation Learning from Multiple Tasks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Junkun Chen, Renjie Zheng, Xipeng Qiu","submitted_at":"2018-04-22T17:13:06Z","abstract_excerpt":"Distributed representation plays an important role in deep learning based natural language processing. However, the representation of a sentence often varies in different tasks, which is usually learned from scratch and suffers from the limited amounts of training data. In this paper, we claim that a good sentence representation should be invariant and can benefit the various subsequent tasks. To achieve this purpose, we propose a new scheme of information sharing for multi-task learning. More specifically, all tasks share the same sentence representation and each task can select the task-spec"},"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":"1804.08139","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-04-22T17:13:06Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"44f4b3c7f1163251aa30acab1d30a2fe399d071043c8070cf6e27d8e4e4db7e4","abstract_canon_sha256":"0444b1c3dc4e0a1f01d3001679e3c9b41dfd2668a2024d65b57bd5c463443d26"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:17:49.429816Z","signature_b64":"WeZ04t8sYwgvL00mFszuxfJLUjA0vtuKMIo9FHn7x/do8jnT1UoK18thbbHuA41SpLGwDL53nE3iN0RpyynTBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"95714094b258044ea958f13dd5e7b4c29e2abfbcae0b164f4d445cc312b1f595","last_reissued_at":"2026-05-18T00:17:49.429214Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:17:49.429214Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Same Representation, Different Attentions: Shareable Sentence Representation Learning from Multiple Tasks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Junkun Chen, Renjie Zheng, Xipeng Qiu","submitted_at":"2018-04-22T17:13:06Z","abstract_excerpt":"Distributed representation plays an important role in deep learning based natural language processing. However, the representation of a sentence often varies in different tasks, which is usually learned from scratch and suffers from the limited amounts of training data. In this paper, we claim that a good sentence representation should be invariant and can benefit the various subsequent tasks. To achieve this purpose, we propose a new scheme of information sharing for multi-task learning. More specifically, all tasks share the same sentence representation and each task can select the task-spec"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.08139","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":""},"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":"1804.08139","created_at":"2026-05-18T00:17:49.429323+00:00"},{"alias_kind":"arxiv_version","alias_value":"1804.08139v1","created_at":"2026-05-18T00:17:49.429323+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.08139","created_at":"2026-05-18T00:17:49.429323+00:00"},{"alias_kind":"pith_short_12","alias_value":"SVYUBFFSLACE","created_at":"2026-05-18T12:32:53.628368+00:00"},{"alias_kind":"pith_short_16","alias_value":"SVYUBFFSLACE5KKY","created_at":"2026-05-18T12:32:53.628368+00:00"},{"alias_kind":"pith_short_8","alias_value":"SVYUBFFS","created_at":"2026-05-18T12:32:53.628368+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/SVYUBFFSLACE5KKY6E65LZ5UYK","json":"https://pith.science/pith/SVYUBFFSLACE5KKY6E65LZ5UYK.json","graph_json":"https://pith.science/api/pith-number/SVYUBFFSLACE5KKY6E65LZ5UYK/graph.json","events_json":"https://pith.science/api/pith-number/SVYUBFFSLACE5KKY6E65LZ5UYK/events.json","paper":"https://pith.science/paper/SVYUBFFS"},"agent_actions":{"view_html":"https://pith.science/pith/SVYUBFFSLACE5KKY6E65LZ5UYK","download_json":"https://pith.science/pith/SVYUBFFSLACE5KKY6E65LZ5UYK.json","view_paper":"https://pith.science/paper/SVYUBFFS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1804.08139&json=true","fetch_graph":"https://pith.science/api/pith-number/SVYUBFFSLACE5KKY6E65LZ5UYK/graph.json","fetch_events":"https://pith.science/api/pith-number/SVYUBFFSLACE5KKY6E65LZ5UYK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SVYUBFFSLACE5KKY6E65LZ5UYK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SVYUBFFSLACE5KKY6E65LZ5UYK/action/storage_attestation","attest_author":"https://pith.science/pith/SVYUBFFSLACE5KKY6E65LZ5UYK/action/author_attestation","sign_citation":"https://pith.science/pith/SVYUBFFSLACE5KKY6E65LZ5UYK/action/citation_signature","submit_replication":"https://pith.science/pith/SVYUBFFSLACE5KKY6E65LZ5UYK/action/replication_record"}},"created_at":"2026-05-18T00:17:49.429323+00:00","updated_at":"2026-05-18T00:17:49.429323+00:00"}