{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:LFBNW42ZYR7EGVIG4TUCXFVN5X","short_pith_number":"pith:LFBNW42Z","canonical_record":{"source":{"id":"1810.06695","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2018-10-10T09:57:32Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"b42d8fc98b870f9bc521c62255e29f5f88a84016471717dd96381a72e4676f9b","abstract_canon_sha256":"908174fae5c0d4e9a541191ab9a483288434e47a8f1d2099b7af6192303154cb"},"schema_version":"1.0"},"canonical_sha256":"5942db7359c47e435506e4e82b96adedc5a95150b3390685d9c3145d807f49d1","source":{"kind":"arxiv","id":"1810.06695","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.06695","created_at":"2026-05-18T00:03:11Z"},{"alias_kind":"arxiv_version","alias_value":"1810.06695v1","created_at":"2026-05-18T00:03:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.06695","created_at":"2026-05-18T00:03:11Z"},{"alias_kind":"pith_short_12","alias_value":"LFBNW42ZYR7E","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_16","alias_value":"LFBNW42ZYR7EGVIG","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_8","alias_value":"LFBNW42Z","created_at":"2026-05-18T12:32:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:LFBNW42ZYR7EGVIG4TUCXFVN5X","target":"record","payload":{"canonical_record":{"source":{"id":"1810.06695","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2018-10-10T09:57:32Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"b42d8fc98b870f9bc521c62255e29f5f88a84016471717dd96381a72e4676f9b","abstract_canon_sha256":"908174fae5c0d4e9a541191ab9a483288434e47a8f1d2099b7af6192303154cb"},"schema_version":"1.0"},"canonical_sha256":"5942db7359c47e435506e4e82b96adedc5a95150b3390685d9c3145d807f49d1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:03:11.899496Z","signature_b64":"hkegUOr/ONk7FrHKSZikVkl/1wET+diz+TRYkruEdWD1M+wYbfaVjOkWUOjnu3j4HaZ79P6c8DDIVAEYjVIhAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5942db7359c47e435506e4e82b96adedc5a95150b3390685d9c3145d807f49d1","last_reissued_at":"2026-05-18T00:03:11.898881Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:03:11.898881Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.06695","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:03:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wYXJV6tS60IJZGW5UabL8IPgG00Ysf0hwFdRi7y31L4IG26PCvYyKtTUiBAVEWrKiX5YbG6tQKdfsp9v2OMDCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T22:38:41.518970Z"},"content_sha256":"2349ae839a652555e4ba8478fd3e45078f9683c0ac889a0637dea024f2f2e2eb","schema_version":"1.0","event_id":"sha256:2349ae839a652555e4ba8478fd3e45078f9683c0ac889a0637dea024f2f2e2eb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:LFBNW42ZYR7EGVIG4TUCXFVN5X","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exploring the Use of Attention within an Neural Machine Translation Decoder States to Translate Idioms","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.CL","authors_text":"Giancarlo D. Salton, John D. Kelleher, Robert J. Ross","submitted_at":"2018-10-10T09:57:32Z","abstract_excerpt":"Idioms pose problems to almost all Machine Translation systems. This type of language is very frequent in day-to-day language use and cannot be simply ignored. The recent interest in memory augmented models in the field of Language Modelling has aided the systems to achieve good results by bridging long-distance dependencies. In this paper we explore the use of such techniques into a Neural Machine Translation system to help in translation of idiomatic language."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.06695","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:03:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qfKBq4gZoDNqMLlMgOAQN/Ks05ARYYR+lj8Twucc7Uub9BNEqVlPIl79Ceyr5sIwJFsVuTVgD7nY9lthSyMaDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T22:38:41.519332Z"},"content_sha256":"0b0b978450d8b088a835b2dbf2e589c8c41915d737446b47bba6fa38a91d389a","schema_version":"1.0","event_id":"sha256:0b0b978450d8b088a835b2dbf2e589c8c41915d737446b47bba6fa38a91d389a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LFBNW42ZYR7EGVIG4TUCXFVN5X/bundle.json","state_url":"https://pith.science/pith/LFBNW42ZYR7EGVIG4TUCXFVN5X/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LFBNW42ZYR7EGVIG4TUCXFVN5X/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":"2026-06-03T22:38:41Z","links":{"resolver":"https://pith.science/pith/LFBNW42ZYR7EGVIG4TUCXFVN5X","bundle":"https://pith.science/pith/LFBNW42ZYR7EGVIG4TUCXFVN5X/bundle.json","state":"https://pith.science/pith/LFBNW42ZYR7EGVIG4TUCXFVN5X/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LFBNW42ZYR7EGVIG4TUCXFVN5X/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:LFBNW42ZYR7EGVIG4TUCXFVN5X","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":"908174fae5c0d4e9a541191ab9a483288434e47a8f1d2099b7af6192303154cb","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2018-10-10T09:57:32Z","title_canon_sha256":"b42d8fc98b870f9bc521c62255e29f5f88a84016471717dd96381a72e4676f9b"},"schema_version":"1.0","source":{"id":"1810.06695","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.06695","created_at":"2026-05-18T00:03:11Z"},{"alias_kind":"arxiv_version","alias_value":"1810.06695v1","created_at":"2026-05-18T00:03:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.06695","created_at":"2026-05-18T00:03:11Z"},{"alias_kind":"pith_short_12","alias_value":"LFBNW42ZYR7E","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_16","alias_value":"LFBNW42ZYR7EGVIG","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_8","alias_value":"LFBNW42Z","created_at":"2026-05-18T12:32:37Z"}],"graph_snapshots":[{"event_id":"sha256:0b0b978450d8b088a835b2dbf2e589c8c41915d737446b47bba6fa38a91d389a","target":"graph","created_at":"2026-05-18T00:03:11Z","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"},"paper":{"abstract_excerpt":"Idioms pose problems to almost all Machine Translation systems. This type of language is very frequent in day-to-day language use and cannot be simply ignored. The recent interest in memory augmented models in the field of Language Modelling has aided the systems to achieve good results by bridging long-distance dependencies. In this paper we explore the use of such techniques into a Neural Machine Translation system to help in translation of idiomatic language.","authors_text":"Giancarlo D. Salton, John D. Kelleher, Robert J. Ross","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2018-10-10T09:57:32Z","title":"Exploring the Use of Attention within an Neural Machine Translation Decoder States to Translate Idioms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.06695","kind":"arxiv","version":1},"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":"sha256:2349ae839a652555e4ba8478fd3e45078f9683c0ac889a0637dea024f2f2e2eb","target":"record","created_at":"2026-05-18T00:03:11Z","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":"908174fae5c0d4e9a541191ab9a483288434e47a8f1d2099b7af6192303154cb","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2018-10-10T09:57:32Z","title_canon_sha256":"b42d8fc98b870f9bc521c62255e29f5f88a84016471717dd96381a72e4676f9b"},"schema_version":"1.0","source":{"id":"1810.06695","kind":"arxiv","version":1}},"canonical_sha256":"5942db7359c47e435506e4e82b96adedc5a95150b3390685d9c3145d807f49d1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5942db7359c47e435506e4e82b96adedc5a95150b3390685d9c3145d807f49d1","first_computed_at":"2026-05-18T00:03:11.898881Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:03:11.898881Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hkegUOr/ONk7FrHKSZikVkl/1wET+diz+TRYkruEdWD1M+wYbfaVjOkWUOjnu3j4HaZ79P6c8DDIVAEYjVIhAQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:03:11.899496Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.06695","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2349ae839a652555e4ba8478fd3e45078f9683c0ac889a0637dea024f2f2e2eb","sha256:0b0b978450d8b088a835b2dbf2e589c8c41915d737446b47bba6fa38a91d389a"],"state_sha256":"23081f40ec1aded8829dbf99fa6771577a8ba8479541db7fbf6ccee0dac5b853"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Amw46ZnbcpFtlM87a7CBgzOOEjIotZGCQui5MGM3gShR02tTHym6l5CMeAD4UhNElAoMpY5cDgK3R6Hz5bhzDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T22:38:41.521425Z","bundle_sha256":"4a84a1fb36503a9eaea0383091228805baf0ee13cd2244666f3d65ed57b006c9"}}