{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:UIRIKUEWAYPGR3KRK3FHJA5NTQ","short_pith_number":"pith:UIRIKUEW","canonical_record":{"source":{"id":"1509.07308","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-09-24T11:00:04Z","cross_cats_sorted":[],"title_canon_sha256":"15039e380bd6a903fa0ef521cde0c0337e58b9a5e6631181cdab814e48ce4f46","abstract_canon_sha256":"3eda3a284c1632fa96c72263b99806313fb48d03e1b29bb82a5ced16653acd8f"},"schema_version":"1.0"},"canonical_sha256":"a222855096061e68ed5156ca7483ad9c0a7543b8a507ff033dceabfa31e0d0b6","source":{"kind":"arxiv","id":"1509.07308","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1509.07308","created_at":"2026-05-18T01:19:53Z"},{"alias_kind":"arxiv_version","alias_value":"1509.07308v2","created_at":"2026-05-18T01:19:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1509.07308","created_at":"2026-05-18T01:19:53Z"},{"alias_kind":"pith_short_12","alias_value":"UIRIKUEWAYPG","created_at":"2026-05-18T12:29:44Z"},{"alias_kind":"pith_short_16","alias_value":"UIRIKUEWAYPGR3KR","created_at":"2026-05-18T12:29:44Z"},{"alias_kind":"pith_short_8","alias_value":"UIRIKUEW","created_at":"2026-05-18T12:29:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:UIRIKUEWAYPGR3KRK3FHJA5NTQ","target":"record","payload":{"canonical_record":{"source":{"id":"1509.07308","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-09-24T11:00:04Z","cross_cats_sorted":[],"title_canon_sha256":"15039e380bd6a903fa0ef521cde0c0337e58b9a5e6631181cdab814e48ce4f46","abstract_canon_sha256":"3eda3a284c1632fa96c72263b99806313fb48d03e1b29bb82a5ced16653acd8f"},"schema_version":"1.0"},"canonical_sha256":"a222855096061e68ed5156ca7483ad9c0a7543b8a507ff033dceabfa31e0d0b6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:19:53.579137Z","signature_b64":"BMdS7CAZB8plbhKjadHWH+CpRHDz0QhBeHaueDYh2LO1ZJaLR3U6KMQjCeOHkwsGQgrnrY/cYkr9uXMtFDXeDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a222855096061e68ed5156ca7483ad9c0a7543b8a507ff033dceabfa31e0d0b6","last_reissued_at":"2026-05-18T01:19:53.578738Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:19:53.578738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1509.07308","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:19:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mcCDlasQdNcSnA804CyGuP9j9cn3QshyKzut7xc+ukG4ayNbiojlB/j8NlBG0rEovEwYg2NY+TbU0ELYg1JyDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T06:15:25.774255Z"},"content_sha256":"f96abae12de3f3079eafede65a870da262005d77e970c694afe1d0bd99594b2c","schema_version":"1.0","event_id":"sha256:f96abae12de3f3079eafede65a870da262005d77e970c694afe1d0bd99594b2c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:UIRIKUEWAYPGR3KRK3FHJA5NTQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bilingual Distributed Word Representations from Document-Aligned Comparable Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ivan Vuli\\'c, Marie-Francine Moens","submitted_at":"2015-09-24T11:00:04Z","abstract_excerpt":"We propose a new model for learning bilingual word representations from non-parallel document-aligned data. Following the recent advances in word representation learning, our model learns dense real-valued word vectors, that is, bilingual word embeddings (BWEs). Unlike prior work on inducing BWEs which heavily relied on parallel sentence-aligned corpora and/or readily available translation resources such as dictionaries, the article reveals that BWEs may be learned solely on the basis of document-aligned comparable data without any additional lexical resources nor syntactic information. We pre"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1509.07308","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:19:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D0+BCzClyKdv2MjurGqNsjfmAiNRV413cJ8HORFu00NHCeH3/VehWdeVwoRjV30Iq/9/Dg3vKHB7vYh0z9WfCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T06:15:25.774932Z"},"content_sha256":"b7347df19e08a9c7f32153e7c42888780a54f1c9a29260b9502a2468b497e2c0","schema_version":"1.0","event_id":"sha256:b7347df19e08a9c7f32153e7c42888780a54f1c9a29260b9502a2468b497e2c0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UIRIKUEWAYPGR3KRK3FHJA5NTQ/bundle.json","state_url":"https://pith.science/pith/UIRIKUEWAYPGR3KRK3FHJA5NTQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UIRIKUEWAYPGR3KRK3FHJA5NTQ/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":"2026-06-05T06:15:25Z","links":{"resolver":"https://pith.science/pith/UIRIKUEWAYPGR3KRK3FHJA5NTQ","bundle":"https://pith.science/pith/UIRIKUEWAYPGR3KRK3FHJA5NTQ/bundle.json","state":"https://pith.science/pith/UIRIKUEWAYPGR3KRK3FHJA5NTQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UIRIKUEWAYPGR3KRK3FHJA5NTQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:UIRIKUEWAYPGR3KRK3FHJA5NTQ","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":"3eda3a284c1632fa96c72263b99806313fb48d03e1b29bb82a5ced16653acd8f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-09-24T11:00:04Z","title_canon_sha256":"15039e380bd6a903fa0ef521cde0c0337e58b9a5e6631181cdab814e48ce4f46"},"schema_version":"1.0","source":{"id":"1509.07308","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1509.07308","created_at":"2026-05-18T01:19:53Z"},{"alias_kind":"arxiv_version","alias_value":"1509.07308v2","created_at":"2026-05-18T01:19:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1509.07308","created_at":"2026-05-18T01:19:53Z"},{"alias_kind":"pith_short_12","alias_value":"UIRIKUEWAYPG","created_at":"2026-05-18T12:29:44Z"},{"alias_kind":"pith_short_16","alias_value":"UIRIKUEWAYPGR3KR","created_at":"2026-05-18T12:29:44Z"},{"alias_kind":"pith_short_8","alias_value":"UIRIKUEW","created_at":"2026-05-18T12:29:44Z"}],"graph_snapshots":[{"event_id":"sha256:b7347df19e08a9c7f32153e7c42888780a54f1c9a29260b9502a2468b497e2c0","target":"graph","created_at":"2026-05-18T01:19:53Z","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":"We propose a new model for learning bilingual word representations from non-parallel document-aligned data. Following the recent advances in word representation learning, our model learns dense real-valued word vectors, that is, bilingual word embeddings (BWEs). Unlike prior work on inducing BWEs which heavily relied on parallel sentence-aligned corpora and/or readily available translation resources such as dictionaries, the article reveals that BWEs may be learned solely on the basis of document-aligned comparable data without any additional lexical resources nor syntactic information. We pre","authors_text":"Ivan Vuli\\'c, Marie-Francine Moens","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-09-24T11:00:04Z","title":"Bilingual Distributed Word Representations from Document-Aligned Comparable Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1509.07308","kind":"arxiv","version":2},"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:f96abae12de3f3079eafede65a870da262005d77e970c694afe1d0bd99594b2c","target":"record","created_at":"2026-05-18T01:19:53Z","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":"3eda3a284c1632fa96c72263b99806313fb48d03e1b29bb82a5ced16653acd8f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2015-09-24T11:00:04Z","title_canon_sha256":"15039e380bd6a903fa0ef521cde0c0337e58b9a5e6631181cdab814e48ce4f46"},"schema_version":"1.0","source":{"id":"1509.07308","kind":"arxiv","version":2}},"canonical_sha256":"a222855096061e68ed5156ca7483ad9c0a7543b8a507ff033dceabfa31e0d0b6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a222855096061e68ed5156ca7483ad9c0a7543b8a507ff033dceabfa31e0d0b6","first_computed_at":"2026-05-18T01:19:53.578738Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:19:53.578738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BMdS7CAZB8plbhKjadHWH+CpRHDz0QhBeHaueDYh2LO1ZJaLR3U6KMQjCeOHkwsGQgrnrY/cYkr9uXMtFDXeDA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:19:53.579137Z","signed_message":"canonical_sha256_bytes"},"source_id":"1509.07308","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f96abae12de3f3079eafede65a870da262005d77e970c694afe1d0bd99594b2c","sha256:b7347df19e08a9c7f32153e7c42888780a54f1c9a29260b9502a2468b497e2c0"],"state_sha256":"8eecfaa3988343280c41d2316bc222ecf6de9ddbc1e71b5b572a5aba9434ce07"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QisYSvbAtZ8atb+5ey3NXuMQEM20hZq2mqN06F1WqFXbqzcNxWqYM0QWJvMvX1w9agocFMt7J92gcXEsvlwKBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T06:15:25.778041Z","bundle_sha256":"520b00eb95d799ac0aa9b5b72f1beb63e21113eb6130c8b5218d8d984fb7ea90"}}