{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:ASI366PQASV22UGBNOMYYWYQA5","short_pith_number":"pith:ASI366PQ","schema_version":"1.0","canonical_sha256":"0491bf79f004abad50c16b998c5b10076dc66ae6f344bc35f91fd2215cf1bdc9","source":{"kind":"arxiv","id":"1512.08756","version":5},"attestation_state":"computed","paper":{"title":"Feed-Forward Networks with Attention Can Solve Some Long-Term Memory Problems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.LG","authors_text":"Colin Raffel, Daniel P. W. Ellis","submitted_at":"2015-12-29T19:03:43Z","abstract_excerpt":"We propose a simplified model of attention which is applicable to feed-forward neural networks and demonstrate that the resulting model can solve the synthetic \"addition\" and \"multiplication\" long-term memory problems for sequence lengths which are both longer and more widely varying than the best published results for these tasks."},"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":"1512.08756","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2015-12-29T19:03:43Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"e8b4bc2bd91ed7d440ae5fa9f773c96a9f724dcbef8cde38b0b00a54dadb4245","abstract_canon_sha256":"fda4b83bcf7048e4d34ac4c5a43609b29d02d4a51ac2a5e78b2b1d32f21f7f10"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:04:21.784689Z","signature_b64":"ydmozrWo9XeRCPVpGNq33+HmBkUun6RftB/ylruQdtz2xwCgb02NoPjrwkdd/7OfqvF3fzLhKtzlvUyv1BDgDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0491bf79f004abad50c16b998c5b10076dc66ae6f344bc35f91fd2215cf1bdc9","last_reissued_at":"2026-05-18T01:04:21.784132Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:04:21.784132Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Feed-Forward Networks with Attention Can Solve Some Long-Term Memory Problems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.LG","authors_text":"Colin Raffel, Daniel P. W. Ellis","submitted_at":"2015-12-29T19:03:43Z","abstract_excerpt":"We propose a simplified model of attention which is applicable to feed-forward neural networks and demonstrate that the resulting model can solve the synthetic \"addition\" and \"multiplication\" long-term memory problems for sequence lengths which are both longer and more widely varying than the best published results for these tasks."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1512.08756","kind":"arxiv","version":5},"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":"1512.08756","created_at":"2026-05-18T01:04:21.784224+00:00"},{"alias_kind":"arxiv_version","alias_value":"1512.08756v5","created_at":"2026-05-18T01:04:21.784224+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1512.08756","created_at":"2026-05-18T01:04:21.784224+00:00"},{"alias_kind":"pith_short_12","alias_value":"ASI366PQASV2","created_at":"2026-05-18T12:29:10.953037+00:00"},{"alias_kind":"pith_short_16","alias_value":"ASI366PQASV22UGB","created_at":"2026-05-18T12:29:10.953037+00:00"},{"alias_kind":"pith_short_8","alias_value":"ASI366PQ","created_at":"2026-05-18T12:29:10.953037+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"1907.04294","citing_title":"An Attention Mechanism for Musical Instrument Recognition","ref_index":41,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ASI366PQASV22UGBNOMYYWYQA5","json":"https://pith.science/pith/ASI366PQASV22UGBNOMYYWYQA5.json","graph_json":"https://pith.science/api/pith-number/ASI366PQASV22UGBNOMYYWYQA5/graph.json","events_json":"https://pith.science/api/pith-number/ASI366PQASV22UGBNOMYYWYQA5/events.json","paper":"https://pith.science/paper/ASI366PQ"},"agent_actions":{"view_html":"https://pith.science/pith/ASI366PQASV22UGBNOMYYWYQA5","download_json":"https://pith.science/pith/ASI366PQASV22UGBNOMYYWYQA5.json","view_paper":"https://pith.science/paper/ASI366PQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1512.08756&json=true","fetch_graph":"https://pith.science/api/pith-number/ASI366PQASV22UGBNOMYYWYQA5/graph.json","fetch_events":"https://pith.science/api/pith-number/ASI366PQASV22UGBNOMYYWYQA5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ASI366PQASV22UGBNOMYYWYQA5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ASI366PQASV22UGBNOMYYWYQA5/action/storage_attestation","attest_author":"https://pith.science/pith/ASI366PQASV22UGBNOMYYWYQA5/action/author_attestation","sign_citation":"https://pith.science/pith/ASI366PQASV22UGBNOMYYWYQA5/action/citation_signature","submit_replication":"https://pith.science/pith/ASI366PQASV22UGBNOMYYWYQA5/action/replication_record"}},"created_at":"2026-05-18T01:04:21.784224+00:00","updated_at":"2026-05-18T01:04:21.784224+00:00"}