{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:ENCQDSPWIOCLU63D3XKOUMUQV2","short_pith_number":"pith:ENCQDSPW","canonical_record":{"source":{"id":"1911.10677","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-25T03:08:42Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"969fe44ba31dacc49068d092623204b493d112ce4a914c5e865852591ccdb44a","abstract_canon_sha256":"135a5ff703d96d118600b8a5c9f237a0c8ed0e47307e6b10a208446d48339cbe"},"schema_version":"1.0"},"canonical_sha256":"234501c9f64384ba7b63ddd4ea3290ae9eb402ca1aef5396b13627edf2a931e6","source":{"kind":"arxiv","id":"1911.10677","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.10677","created_at":"2026-07-05T00:22:43Z"},{"alias_kind":"arxiv_version","alias_value":"1911.10677v1","created_at":"2026-07-05T00:22:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.10677","created_at":"2026-07-05T00:22:43Z"},{"alias_kind":"pith_short_12","alias_value":"ENCQDSPWIOCL","created_at":"2026-07-05T00:22:43Z"},{"alias_kind":"pith_short_16","alias_value":"ENCQDSPWIOCLU63D","created_at":"2026-07-05T00:22:43Z"},{"alias_kind":"pith_short_8","alias_value":"ENCQDSPW","created_at":"2026-07-05T00:22:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:ENCQDSPWIOCLU63D3XKOUMUQV2","target":"record","payload":{"canonical_record":{"source":{"id":"1911.10677","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-25T03:08:42Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"969fe44ba31dacc49068d092623204b493d112ce4a914c5e865852591ccdb44a","abstract_canon_sha256":"135a5ff703d96d118600b8a5c9f237a0c8ed0e47307e6b10a208446d48339cbe"},"schema_version":"1.0"},"canonical_sha256":"234501c9f64384ba7b63ddd4ea3290ae9eb402ca1aef5396b13627edf2a931e6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:22:43.936710Z","signature_b64":"ik73WMm7S/6LXkNaRNvfhfcnNs45rBunOkjh4jCxyw97D1HKCugJ7iflXyzTJOtDBUsj/Yjs0S1UCZcz2/X2Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"234501c9f64384ba7b63ddd4ea3290ae9eb402ca1aef5396b13627edf2a931e6","last_reissued_at":"2026-07-05T00:22:43.936294Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:22:43.936294Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1911.10677","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":"2026-07-05T00:22:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZXpEfaD+czkRXeTxI2u8hv8iH9Md4j2sRnSatT/tTiD8jD/mkRU8LCUrZIoDVqbx68NoXx3CivRjZI7qil2jBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T05:41:22.689697Z"},"content_sha256":"f72538b59604e039e3345305a1c20114fff4188c06fef964579368b59d9a2484","schema_version":"1.0","event_id":"sha256:f72538b59604e039e3345305a1c20114fff4188c06fef964579368b59d9a2484"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:ENCQDSPWIOCLU63D3XKOUMUQV2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Non-autoregressive Transformer by Position Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Hao Zhou, Jiajun Chen, Jiangtao Feng, Lei Li, Mingxuan Wang, Shujian Huang, Yu Bao","submitted_at":"2019-11-25T03:08:42Z","abstract_excerpt":"Non-autoregressive models are promising on various text generation tasks. Previous work hardly considers to explicitly model the positions of generated words. However, position modeling is an essential problem in non-autoregressive text generation. In this study, we propose PNAT, which incorporates positions as a latent variable into the text generative process. Experimental results show that PNAT achieves top results on machine translation and paraphrase generation tasks, outperforming several strong baselines."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.10677","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/1911.10677/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":"2026-07-05T00:22:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+lET+fG49ddyzpIcrRJH0/3kQl1A9LlGG6ljhMXG6ytkZP1NM3qJ6ZpxuQL4F2VW6nlG0DxH3JL2lqReSqblDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T05:41:22.690446Z"},"content_sha256":"95ea8277d3eb940cac1a5149763f547e3dbaaba689c3d4bb141edb19747f1b5f","schema_version":"1.0","event_id":"sha256:95ea8277d3eb940cac1a5149763f547e3dbaaba689c3d4bb141edb19747f1b5f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ENCQDSPWIOCLU63D3XKOUMUQV2/bundle.json","state_url":"https://pith.science/pith/ENCQDSPWIOCLU63D3XKOUMUQV2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ENCQDSPWIOCLU63D3XKOUMUQV2/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":"2026-08-05T05:41:22Z","links":{"resolver":"https://pith.science/pith/ENCQDSPWIOCLU63D3XKOUMUQV2","bundle":"https://pith.science/pith/ENCQDSPWIOCLU63D3XKOUMUQV2/bundle.json","state":"https://pith.science/pith/ENCQDSPWIOCLU63D3XKOUMUQV2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ENCQDSPWIOCLU63D3XKOUMUQV2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ENCQDSPWIOCLU63D3XKOUMUQV2","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":"135a5ff703d96d118600b8a5c9f237a0c8ed0e47307e6b10a208446d48339cbe","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-25T03:08:42Z","title_canon_sha256":"969fe44ba31dacc49068d092623204b493d112ce4a914c5e865852591ccdb44a"},"schema_version":"1.0","source":{"id":"1911.10677","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1911.10677","created_at":"2026-07-05T00:22:43Z"},{"alias_kind":"arxiv_version","alias_value":"1911.10677v1","created_at":"2026-07-05T00:22:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1911.10677","created_at":"2026-07-05T00:22:43Z"},{"alias_kind":"pith_short_12","alias_value":"ENCQDSPWIOCL","created_at":"2026-07-05T00:22:43Z"},{"alias_kind":"pith_short_16","alias_value":"ENCQDSPWIOCLU63D","created_at":"2026-07-05T00:22:43Z"},{"alias_kind":"pith_short_8","alias_value":"ENCQDSPW","created_at":"2026-07-05T00:22:43Z"}],"graph_snapshots":[{"event_id":"sha256:95ea8277d3eb940cac1a5149763f547e3dbaaba689c3d4bb141edb19747f1b5f","target":"graph","created_at":"2026-07-05T00:22:43Z","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/1911.10677/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Non-autoregressive models are promising on various text generation tasks. Previous work hardly considers to explicitly model the positions of generated words. However, position modeling is an essential problem in non-autoregressive text generation. In this study, we propose PNAT, which incorporates positions as a latent variable into the text generative process. Experimental results show that PNAT achieves top results on machine translation and paraphrase generation tasks, outperforming several strong baselines.","authors_text":"Hao Zhou, Jiajun Chen, Jiangtao Feng, Lei Li, Mingxuan Wang, Shujian Huang, Yu Bao","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-25T03:08:42Z","title":"Non-autoregressive Transformer by Position Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1911.10677","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:f72538b59604e039e3345305a1c20114fff4188c06fef964579368b59d9a2484","target":"record","created_at":"2026-07-05T00:22:43Z","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":"135a5ff703d96d118600b8a5c9f237a0c8ed0e47307e6b10a208446d48339cbe","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-11-25T03:08:42Z","title_canon_sha256":"969fe44ba31dacc49068d092623204b493d112ce4a914c5e865852591ccdb44a"},"schema_version":"1.0","source":{"id":"1911.10677","kind":"arxiv","version":1}},"canonical_sha256":"234501c9f64384ba7b63ddd4ea3290ae9eb402ca1aef5396b13627edf2a931e6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"234501c9f64384ba7b63ddd4ea3290ae9eb402ca1aef5396b13627edf2a931e6","first_computed_at":"2026-07-05T00:22:43.936294Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:22:43.936294Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ik73WMm7S/6LXkNaRNvfhfcnNs45rBunOkjh4jCxyw97D1HKCugJ7iflXyzTJOtDBUsj/Yjs0S1UCZcz2/X2Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:22:43.936710Z","signed_message":"canonical_sha256_bytes"},"source_id":"1911.10677","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f72538b59604e039e3345305a1c20114fff4188c06fef964579368b59d9a2484","sha256:95ea8277d3eb940cac1a5149763f547e3dbaaba689c3d4bb141edb19747f1b5f"],"state_sha256":"88ed954a305c358344913484e64952ebed51dc52f8c605f004fef7bcf0774efe"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xl/lLIPFFckLxjJbeRH46BBM563zpTKPYRPIf7fiLfycTimXRpDMhFUQfKGDdmTDCZMCbEcCQ/z1zK8u6EWHAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T05:41:22.694959Z","bundle_sha256":"36a1761557162604332a0b077c0f070f733c303f038ee357b25c62c2bfa2fa06"}}