{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:ELO6OBXGZ63M4HFLV6HLSHVGUZ","short_pith_number":"pith:ELO6OBXG","canonical_record":{"source":{"id":"2005.14489","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-29T10:20:48Z","cross_cats_sorted":[],"title_canon_sha256":"bbf2903785c6c1d638f395ab51a2cb44779ab4dd73a9df24bd809f2e058dd480","abstract_canon_sha256":"6288a88418521d36c09689c430895f0c32bdefd0b71b980f0c69f65870ed87a7"},"schema_version":"1.0"},"canonical_sha256":"22dde706e6cfb6ce1cabaf8eb91ea6a66933b82bedb49c5fa42c1f92be68e257","source":{"kind":"arxiv","id":"2005.14489","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.14489","created_at":"2026-07-05T01:06:37Z"},{"alias_kind":"arxiv_version","alias_value":"2005.14489v1","created_at":"2026-07-05T01:06:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.14489","created_at":"2026-07-05T01:06:37Z"},{"alias_kind":"pith_short_12","alias_value":"ELO6OBXGZ63M","created_at":"2026-07-05T01:06:37Z"},{"alias_kind":"pith_short_16","alias_value":"ELO6OBXGZ63M4HFL","created_at":"2026-07-05T01:06:37Z"},{"alias_kind":"pith_short_8","alias_value":"ELO6OBXG","created_at":"2026-07-05T01:06:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:ELO6OBXGZ63M4HFLV6HLSHVGUZ","target":"record","payload":{"canonical_record":{"source":{"id":"2005.14489","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-29T10:20:48Z","cross_cats_sorted":[],"title_canon_sha256":"bbf2903785c6c1d638f395ab51a2cb44779ab4dd73a9df24bd809f2e058dd480","abstract_canon_sha256":"6288a88418521d36c09689c430895f0c32bdefd0b71b980f0c69f65870ed87a7"},"schema_version":"1.0"},"canonical_sha256":"22dde706e6cfb6ce1cabaf8eb91ea6a66933b82bedb49c5fa42c1f92be68e257","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:06:37.350945Z","signature_b64":"4LCYgzZCt6bM2p8dO2rk+iENdvx2ImkaWZRksK9pbbWqPMHnWx+WhD+Zpeie7hwRQEl6pMRbNEkc0xND08KDAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"22dde706e6cfb6ce1cabaf8eb91ea6a66933b82bedb49c5fa42c1f92be68e257","last_reissued_at":"2026-07-05T01:06:37.350481Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:06:37.350481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2005.14489","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":"2026-07-05T01:06:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N+J1uNLbM1znJIqS6FoVnihf7R3HrOINJS/gj20B46ysPpP8w1/qYCG4j+tgsrTaLpZ0+yh/JZ6CdS3diYq4AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T06:00:49.285572Z"},"content_sha256":"1a91deb331800867230cefd10e1849521c3afdd54ccd542bcf6f5097e0a9437a","schema_version":"1.0","event_id":"sha256:1a91deb331800867230cefd10e1849521c3afdd54ccd542bcf6f5097e0a9437a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:ELO6OBXGZ63M4HFLV6HLSHVGUZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural Simultaneous Speech Translation Using Alignment-Based Chunking","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Evgeny Matusov, Patrick Wilken, Pavel Golik, Tamer Alkhouli","submitted_at":"2020-05-29T10:20:48Z","abstract_excerpt":"In simultaneous machine translation, the objective is to determine when to produce a partial translation given a continuous stream of source words, with a trade-off between latency and quality. We propose a neural machine translation (NMT) model that makes dynamic decisions when to continue feeding on input or generate output words. The model is composed of two main components: one to dynamically decide on ending a source chunk, and another that translates the consumed chunk. We train the components jointly and in a manner consistent with the inference conditions. To generate chunked training "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.14489","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2005.14489/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T01:06:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rdoMI55IlHJyajsleHJraXxaq46ZqPR/L0bvE7iC1byJdZbnWZOtC5MJTdxaoohy+JAFbb93/TAiIdGMDUPXDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T06:00:49.286444Z"},"content_sha256":"16d31225c97a4807a8ad439cb7dfa3ec35658f7dcd71d7e94dbffc553ea20425","schema_version":"1.0","event_id":"sha256:16d31225c97a4807a8ad439cb7dfa3ec35658f7dcd71d7e94dbffc553ea20425"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ/bundle.json","state_url":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ/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":"2026-08-04T06:00:49Z","links":{"resolver":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ","bundle":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ/bundle.json","state":"https://pith.science/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ELO6OBXGZ63M4HFLV6HLSHVGUZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:ELO6OBXGZ63M4HFLV6HLSHVGUZ","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":"6288a88418521d36c09689c430895f0c32bdefd0b71b980f0c69f65870ed87a7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-29T10:20:48Z","title_canon_sha256":"bbf2903785c6c1d638f395ab51a2cb44779ab4dd73a9df24bd809f2e058dd480"},"schema_version":"1.0","source":{"id":"2005.14489","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2005.14489","created_at":"2026-07-05T01:06:37Z"},{"alias_kind":"arxiv_version","alias_value":"2005.14489v1","created_at":"2026-07-05T01:06:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2005.14489","created_at":"2026-07-05T01:06:37Z"},{"alias_kind":"pith_short_12","alias_value":"ELO6OBXGZ63M","created_at":"2026-07-05T01:06:37Z"},{"alias_kind":"pith_short_16","alias_value":"ELO6OBXGZ63M4HFL","created_at":"2026-07-05T01:06:37Z"},{"alias_kind":"pith_short_8","alias_value":"ELO6OBXG","created_at":"2026-07-05T01:06:37Z"}],"graph_snapshots":[{"event_id":"sha256:16d31225c97a4807a8ad439cb7dfa3ec35658f7dcd71d7e94dbffc553ea20425","target":"graph","created_at":"2026-07-05T01:06:37Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2005.14489/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In simultaneous machine translation, the objective is to determine when to produce a partial translation given a continuous stream of source words, with a trade-off between latency and quality. We propose a neural machine translation (NMT) model that makes dynamic decisions when to continue feeding on input or generate output words. The model is composed of two main components: one to dynamically decide on ending a source chunk, and another that translates the consumed chunk. We train the components jointly and in a manner consistent with the inference conditions. To generate chunked training ","authors_text":"Evgeny Matusov, Patrick Wilken, Pavel Golik, Tamer Alkhouli","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-29T10:20:48Z","title":"Neural Simultaneous Speech Translation Using Alignment-Based Chunking"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2005.14489","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":"sha256:1a91deb331800867230cefd10e1849521c3afdd54ccd542bcf6f5097e0a9437a","target":"record","created_at":"2026-07-05T01:06:37Z","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":"6288a88418521d36c09689c430895f0c32bdefd0b71b980f0c69f65870ed87a7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-29T10:20:48Z","title_canon_sha256":"bbf2903785c6c1d638f395ab51a2cb44779ab4dd73a9df24bd809f2e058dd480"},"schema_version":"1.0","source":{"id":"2005.14489","kind":"arxiv","version":1}},"canonical_sha256":"22dde706e6cfb6ce1cabaf8eb91ea6a66933b82bedb49c5fa42c1f92be68e257","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"22dde706e6cfb6ce1cabaf8eb91ea6a66933b82bedb49c5fa42c1f92be68e257","first_computed_at":"2026-07-05T01:06:37.350481Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:06:37.350481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4LCYgzZCt6bM2p8dO2rk+iENdvx2ImkaWZRksK9pbbWqPMHnWx+WhD+Zpeie7hwRQEl6pMRbNEkc0xND08KDAw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:06:37.350945Z","signed_message":"canonical_sha256_bytes"},"source_id":"2005.14489","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1a91deb331800867230cefd10e1849521c3afdd54ccd542bcf6f5097e0a9437a","sha256:16d31225c97a4807a8ad439cb7dfa3ec35658f7dcd71d7e94dbffc553ea20425"],"state_sha256":"99df825951dcd39d8fce50767987e5acbbc737c2c3b719c3c34a2387677ecc19"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+WQ7dF0t7G19Ax1TUu81GV7klvd5JyPE4krVIjd1ljop00GHlaZZqlVEwfAURLcruj9jArA562i0c/aRAqpFDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T06:00:49.291680Z","bundle_sha256":"89d0a7392856b5aaa8e6e91c9aed7e72f437c834801ffda589e901ce1f2e5c3d"}}