{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:YKE3A6D4DK4SI3OQO6XVO5UTWA","short_pith_number":"pith:YKE3A6D4","canonical_record":{"source":{"id":"2009.07177","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-15T15:30:14Z","cross_cats_sorted":[],"title_canon_sha256":"4c5f837f177809a1c0c7ca1dc9037e18995ddc0b43aa10b7be92a1becadd0634","abstract_canon_sha256":"4610c6d3c813967d86ba7c71d430706f7092ac67bf5ad135e7549f2254d98fbd"},"schema_version":"1.0"},"canonical_sha256":"c289b0787c1ab9246dd077af577693b0302883cd68ed0da8364470ab7bdb3d83","source":{"kind":"arxiv","id":"2009.07177","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.07177","created_at":"2026-07-05T01:35:41Z"},{"alias_kind":"arxiv_version","alias_value":"2009.07177v1","created_at":"2026-07-05T01:35:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.07177","created_at":"2026-07-05T01:35:41Z"},{"alias_kind":"pith_short_12","alias_value":"YKE3A6D4DK4S","created_at":"2026-07-05T01:35:41Z"},{"alias_kind":"pith_short_16","alias_value":"YKE3A6D4DK4SI3OQ","created_at":"2026-07-05T01:35:41Z"},{"alias_kind":"pith_short_8","alias_value":"YKE3A6D4","created_at":"2026-07-05T01:35:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:YKE3A6D4DK4SI3OQO6XVO5UTWA","target":"record","payload":{"canonical_record":{"source":{"id":"2009.07177","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-15T15:30:14Z","cross_cats_sorted":[],"title_canon_sha256":"4c5f837f177809a1c0c7ca1dc9037e18995ddc0b43aa10b7be92a1becadd0634","abstract_canon_sha256":"4610c6d3c813967d86ba7c71d430706f7092ac67bf5ad135e7549f2254d98fbd"},"schema_version":"1.0"},"canonical_sha256":"c289b0787c1ab9246dd077af577693b0302883cd68ed0da8364470ab7bdb3d83","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:35:41.358512Z","signature_b64":"o/5Zbqhvo70xrCI1zs+Sc0reqH+NM4NGUdIIJXoC7MnSmCz32TxVDoQYpwpVVmSCv3aQ7O3emPRaxk8gl9RECQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c289b0787c1ab9246dd077af577693b0302883cd68ed0da8364470ab7bdb3d83","last_reissued_at":"2026-07-05T01:35:41.358119Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:35:41.358119Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2009.07177","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":"2026-07-05T01:35:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FUwntB7XOc5L+VHckTKmJUUK+3fw/9iPcaWzKElEZuGsrbktSKPnoHESmeLJ8s8yqKCYuQpI9FY0PD8B+mMpBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T07:03:40.404108Z"},"content_sha256":"3d3dbeb5a0b175e19146f2e3b4064d2ff2b19db831413e63d4b623b36663fbe4","schema_version":"1.0","event_id":"sha256:3d3dbeb5a0b175e19146f2e3b4064d2ff2b19db831413e63d4b623b36663fbe4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:YKE3A6D4DK4SI3OQO6XVO5UTWA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jason Lee, Kyunghyun Cho, Raphael Shu","submitted_at":"2020-09-15T15:30:14Z","abstract_excerpt":"We propose an efficient inference procedure for non-autoregressive machine translation that iteratively refines translation purely in the continuous space. Given a continuous latent variable model for machine translation (Shu et al., 2020), we train an inference network to approximate the gradient of the marginal log probability of the target sentence, using only the latent variable as input. This allows us to use gradient-based optimization to find the target sentence at inference time that approximately maximizes its marginal probability. As each refinement step only involves computation in "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.07177","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/2009.07177/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":"2026-07-05T01:35:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DZ6MkYThhCcZOPLC/WgHvDbZOB3XMlo60kfVCwCXcPWyAy13Lp5/pf1azHF4ZecGnCQRUx0IAxpRkdSpLRtsDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T07:03:40.405757Z"},"content_sha256":"8dbb7a2dd23cee7d0a2e1898896cec6ca5de3fd8d0c3b93c5670ad0fb0bc4862","schema_version":"1.0","event_id":"sha256:8dbb7a2dd23cee7d0a2e1898896cec6ca5de3fd8d0c3b93c5670ad0fb0bc4862"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YKE3A6D4DK4SI3OQO6XVO5UTWA/bundle.json","state_url":"https://pith.science/pith/YKE3A6D4DK4SI3OQO6XVO5UTWA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YKE3A6D4DK4SI3OQO6XVO5UTWA/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":"2026-08-14T07:03:40Z","links":{"resolver":"https://pith.science/pith/YKE3A6D4DK4SI3OQO6XVO5UTWA","bundle":"https://pith.science/pith/YKE3A6D4DK4SI3OQO6XVO5UTWA/bundle.json","state":"https://pith.science/pith/YKE3A6D4DK4SI3OQO6XVO5UTWA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YKE3A6D4DK4SI3OQO6XVO5UTWA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:YKE3A6D4DK4SI3OQO6XVO5UTWA","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":"4610c6d3c813967d86ba7c71d430706f7092ac67bf5ad135e7549f2254d98fbd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-15T15:30:14Z","title_canon_sha256":"4c5f837f177809a1c0c7ca1dc9037e18995ddc0b43aa10b7be92a1becadd0634"},"schema_version":"1.0","source":{"id":"2009.07177","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.07177","created_at":"2026-07-05T01:35:41Z"},{"alias_kind":"arxiv_version","alias_value":"2009.07177v1","created_at":"2026-07-05T01:35:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.07177","created_at":"2026-07-05T01:35:41Z"},{"alias_kind":"pith_short_12","alias_value":"YKE3A6D4DK4S","created_at":"2026-07-05T01:35:41Z"},{"alias_kind":"pith_short_16","alias_value":"YKE3A6D4DK4SI3OQ","created_at":"2026-07-05T01:35:41Z"},{"alias_kind":"pith_short_8","alias_value":"YKE3A6D4","created_at":"2026-07-05T01:35:41Z"}],"graph_snapshots":[{"event_id":"sha256:8dbb7a2dd23cee7d0a2e1898896cec6ca5de3fd8d0c3b93c5670ad0fb0bc4862","target":"graph","created_at":"2026-07-05T01:35:41Z","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/2009.07177/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose an efficient inference procedure for non-autoregressive machine translation that iteratively refines translation purely in the continuous space. Given a continuous latent variable model for machine translation (Shu et al., 2020), we train an inference network to approximate the gradient of the marginal log probability of the target sentence, using only the latent variable as input. This allows us to use gradient-based optimization to find the target sentence at inference time that approximately maximizes its marginal probability. As each refinement step only involves computation in ","authors_text":"Jason Lee, Kyunghyun Cho, Raphael Shu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-15T15:30:14Z","title":"Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.07177","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":"sha256:3d3dbeb5a0b175e19146f2e3b4064d2ff2b19db831413e63d4b623b36663fbe4","target":"record","created_at":"2026-07-05T01:35:41Z","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":"4610c6d3c813967d86ba7c71d430706f7092ac67bf5ad135e7549f2254d98fbd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-15T15:30:14Z","title_canon_sha256":"4c5f837f177809a1c0c7ca1dc9037e18995ddc0b43aa10b7be92a1becadd0634"},"schema_version":"1.0","source":{"id":"2009.07177","kind":"arxiv","version":1}},"canonical_sha256":"c289b0787c1ab9246dd077af577693b0302883cd68ed0da8364470ab7bdb3d83","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c289b0787c1ab9246dd077af577693b0302883cd68ed0da8364470ab7bdb3d83","first_computed_at":"2026-07-05T01:35:41.358119Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:35:41.358119Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"o/5Zbqhvo70xrCI1zs+Sc0reqH+NM4NGUdIIJXoC7MnSmCz32TxVDoQYpwpVVmSCv3aQ7O3emPRaxk8gl9RECQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:35:41.358512Z","signed_message":"canonical_sha256_bytes"},"source_id":"2009.07177","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3d3dbeb5a0b175e19146f2e3b4064d2ff2b19db831413e63d4b623b36663fbe4","sha256:8dbb7a2dd23cee7d0a2e1898896cec6ca5de3fd8d0c3b93c5670ad0fb0bc4862"],"state_sha256":"b498d335636401bc997bf72944b8da88e6593c011e0f8d47483830ae27d17ca2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Pdp33NPP903LDavzNCjLJ2CbA/tpcLxs6drNlmMDdLbYobRwfrOQNrfVc1nJg+I8pIlrChumqxbM99DPDdzHDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T07:03:40.412170Z","bundle_sha256":"01ea881f4472337c6815ef3cfa2c3806bb563d2903eddd981a91dd1b33a5c479"}}