{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:KZNECRM2R7AFQ5GV7AD4PG5BFC","short_pith_number":"pith:KZNECRM2","canonical_record":{"source":{"id":"1301.3614","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2013-01-16T07:56:20Z","cross_cats_sorted":[],"title_canon_sha256":"ded5bb53c1cb36af267c250aab7f5a8c4e111ad1a9770589dfb03f1ef91d270a","abstract_canon_sha256":"136f9058d571a6e136efbc3a754436d0192506552fbfa4e5cbae26e96d79d49f"},"schema_version":"1.0"},"canonical_sha256":"565a41459a8fc05874d5f807c79ba12895de2e8146d49b21ead24e463adc51af","source":{"kind":"arxiv","id":"1301.3614","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.3614","created_at":"2026-05-18T00:46:02Z"},{"alias_kind":"arxiv_version","alias_value":"1301.3614v3","created_at":"2026-05-18T00:46:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.3614","created_at":"2026-05-18T00:46:02Z"},{"alias_kind":"pith_short_12","alias_value":"KZNECRM2R7AF","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_16","alias_value":"KZNECRM2R7AFQ5GV","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_8","alias_value":"KZNECRM2","created_at":"2026-05-18T12:27:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:KZNECRM2R7AFQ5GV7AD4PG5BFC","target":"record","payload":{"canonical_record":{"source":{"id":"1301.3614","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2013-01-16T07:56:20Z","cross_cats_sorted":[],"title_canon_sha256":"ded5bb53c1cb36af267c250aab7f5a8c4e111ad1a9770589dfb03f1ef91d270a","abstract_canon_sha256":"136f9058d571a6e136efbc3a754436d0192506552fbfa4e5cbae26e96d79d49f"},"schema_version":"1.0"},"canonical_sha256":"565a41459a8fc05874d5f807c79ba12895de2e8146d49b21ead24e463adc51af","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:46:02.955155Z","signature_b64":"P9Rcr9i14VD9+OSkt2SeY7Ba5eaJQ44/8pCDyTxVjKX5/ci5AHLEt3oJd2ZKYjos9/94qt95dwgmWnb2/zcMCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"565a41459a8fc05874d5f807c79ba12895de2e8146d49b21ead24e463adc51af","last_reissued_at":"2026-05-18T00:46:02.954649Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:46:02.954649Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1301.3614","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:46:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ce3mMORIkDXAD9jWZl4bN0OaM+lyK9E1q5tO5CJvJkj2Qc6Gsi5vdL34yAItcp2sM/2IrW3L9ZetaqBN7E4CCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T03:53:57.193868Z"},"content_sha256":"620ffb39cf94c2e8e9b5291cab3404310b3aae3401dae083e614e80598e216c5","schema_version":"1.0","event_id":"sha256:620ffb39cf94c2e8e9b5291cab3404310b3aae3401dae083e614e80598e216c5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:KZNECRM2R7AFQ5GV7AD4PG5BFC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Joint Space Neural Probabilistic Language Model for Statistical Machine Translation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Tsuyoshi Okita","submitted_at":"2013-01-16T07:56:20Z","abstract_excerpt":"A neural probabilistic language model (NPLM) provides an idea to achieve the better perplexity than n-gram language model and their smoothed language models. This paper investigates application area in bilingual NLP, specifically Statistical Machine Translation (SMT). We focus on the perspectives that NPLM has potential to open the possibility to complement potentially `huge' monolingual resources into the `resource-constraint' bilingual resources. We introduce an ngram-HMM language model as NPLM using the non-parametric Bayesian construction. In order to facilitate the application to various "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.3614","kind":"arxiv","version":3},"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":"2026-05-18T00:46:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pxwI1ssXaejmvUWZcdLerWTAqBkuYmiPbeKZnSEwm3R5epRmpvtzL8MAvgtNF1jhMwUy+OpxwaFnYBUgTAXoCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T03:53:57.194481Z"},"content_sha256":"3e2ff8bcb140b3f8f4c0599b169a3b383afc0e2822e32d58fab6f615772928b2","schema_version":"1.0","event_id":"sha256:3e2ff8bcb140b3f8f4c0599b169a3b383afc0e2822e32d58fab6f615772928b2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KZNECRM2R7AFQ5GV7AD4PG5BFC/bundle.json","state_url":"https://pith.science/pith/KZNECRM2R7AFQ5GV7AD4PG5BFC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KZNECRM2R7AFQ5GV7AD4PG5BFC/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":"2026-05-30T03:53:57Z","links":{"resolver":"https://pith.science/pith/KZNECRM2R7AFQ5GV7AD4PG5BFC","bundle":"https://pith.science/pith/KZNECRM2R7AFQ5GV7AD4PG5BFC/bundle.json","state":"https://pith.science/pith/KZNECRM2R7AFQ5GV7AD4PG5BFC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KZNECRM2R7AFQ5GV7AD4PG5BFC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:KZNECRM2R7AFQ5GV7AD4PG5BFC","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":"136f9058d571a6e136efbc3a754436d0192506552fbfa4e5cbae26e96d79d49f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2013-01-16T07:56:20Z","title_canon_sha256":"ded5bb53c1cb36af267c250aab7f5a8c4e111ad1a9770589dfb03f1ef91d270a"},"schema_version":"1.0","source":{"id":"1301.3614","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1301.3614","created_at":"2026-05-18T00:46:02Z"},{"alias_kind":"arxiv_version","alias_value":"1301.3614v3","created_at":"2026-05-18T00:46:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1301.3614","created_at":"2026-05-18T00:46:02Z"},{"alias_kind":"pith_short_12","alias_value":"KZNECRM2R7AF","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_16","alias_value":"KZNECRM2R7AFQ5GV","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_8","alias_value":"KZNECRM2","created_at":"2026-05-18T12:27:51Z"}],"graph_snapshots":[{"event_id":"sha256:3e2ff8bcb140b3f8f4c0599b169a3b383afc0e2822e32d58fab6f615772928b2","target":"graph","created_at":"2026-05-18T00:46:02Z","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":"A neural probabilistic language model (NPLM) provides an idea to achieve the better perplexity than n-gram language model and their smoothed language models. This paper investigates application area in bilingual NLP, specifically Statistical Machine Translation (SMT). We focus on the perspectives that NPLM has potential to open the possibility to complement potentially `huge' monolingual resources into the `resource-constraint' bilingual resources. We introduce an ngram-HMM language model as NPLM using the non-parametric Bayesian construction. In order to facilitate the application to various ","authors_text":"Tsuyoshi Okita","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2013-01-16T07:56:20Z","title":"Joint Space Neural Probabilistic Language Model for Statistical Machine Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1301.3614","kind":"arxiv","version":3},"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":"sha256:620ffb39cf94c2e8e9b5291cab3404310b3aae3401dae083e614e80598e216c5","target":"record","created_at":"2026-05-18T00:46:02Z","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":"136f9058d571a6e136efbc3a754436d0192506552fbfa4e5cbae26e96d79d49f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2013-01-16T07:56:20Z","title_canon_sha256":"ded5bb53c1cb36af267c250aab7f5a8c4e111ad1a9770589dfb03f1ef91d270a"},"schema_version":"1.0","source":{"id":"1301.3614","kind":"arxiv","version":3}},"canonical_sha256":"565a41459a8fc05874d5f807c79ba12895de2e8146d49b21ead24e463adc51af","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"565a41459a8fc05874d5f807c79ba12895de2e8146d49b21ead24e463adc51af","first_computed_at":"2026-05-18T00:46:02.954649Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:46:02.954649Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"P9Rcr9i14VD9+OSkt2SeY7Ba5eaJQ44/8pCDyTxVjKX5/ci5AHLEt3oJd2ZKYjos9/94qt95dwgmWnb2/zcMCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:46:02.955155Z","signed_message":"canonical_sha256_bytes"},"source_id":"1301.3614","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:620ffb39cf94c2e8e9b5291cab3404310b3aae3401dae083e614e80598e216c5","sha256:3e2ff8bcb140b3f8f4c0599b169a3b383afc0e2822e32d58fab6f615772928b2"],"state_sha256":"d52cd6585fa6dc4fafa6c934a38ad7f67818a4a19e786d57df9efd2c36238283"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"U2WIQ8dyl2cllOELskNWiAWmPBnRFI1gPTvE+n2Vyaasgnqu9EwGLRus+zOZP5Cc8fZNi+dcC37IRqAHw3keDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T03:53:57.197484Z","bundle_sha256":"fff1dd8bc5662df1a7c2342ed3766bf35c07b14006c8af1b25f07ea0d27b6b33"}}