{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:4S3PHV6E2BBRDSBRCBJ7KZULJL","short_pith_number":"pith:4S3PHV6E","canonical_record":{"source":{"id":"1903.00058","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-02-28T20:33:00Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"d8ac4982e308af57e6cef6859d526aa912ec1f2f82d0c11075c54dbd41f795aa","abstract_canon_sha256":"e1165898da9f84edc12c0dca95ea6c141d61c27b94de7f94398d744a9d20bd25"},"schema_version":"1.0"},"canonical_sha256":"e4b6f3d7c4d04311c8311053f5668b4afd063655fdfebe8c3149403255d5f1f3","source":{"kind":"arxiv","id":"1903.00058","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.00058","created_at":"2026-05-17T23:42:58Z"},{"alias_kind":"arxiv_version","alias_value":"1903.00058v2","created_at":"2026-05-17T23:42:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.00058","created_at":"2026-05-17T23:42:58Z"},{"alias_kind":"pith_short_12","alias_value":"4S3PHV6E2BBR","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4S3PHV6E2BBRDSBR","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4S3PHV6E","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:4S3PHV6E2BBRDSBRCBJ7KZULJL","target":"record","payload":{"canonical_record":{"source":{"id":"1903.00058","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-02-28T20:33:00Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"d8ac4982e308af57e6cef6859d526aa912ec1f2f82d0c11075c54dbd41f795aa","abstract_canon_sha256":"e1165898da9f84edc12c0dca95ea6c141d61c27b94de7f94398d744a9d20bd25"},"schema_version":"1.0"},"canonical_sha256":"e4b6f3d7c4d04311c8311053f5668b4afd063655fdfebe8c3149403255d5f1f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:58.440793Z","signature_b64":"0+TSuWzJjaIv3wTvBUd1LZEhqDzpsxF9gjaGlL+H8bdZ2Lazq8BWj80jAfq5Vb+d87xRdKgKqtnQr5MXBSCwCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e4b6f3d7c4d04311c8311053f5668b4afd063655fdfebe8c3149403255d5f1f3","last_reissued_at":"2026-05-17T23:42:58.440266Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:58.440266Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.00058","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":"2026-05-17T23:42:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"whr2ksam9LSy3Fxvcu+jfvLEg/GO7vEqlDIP17NSZ+ZkJDa8J86253eeOs/aihazJ/lxKTIrDErzu7kWCLyvCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T15:57:37.644096Z"},"content_sha256":"72a0cff6811ea1b05c742468858e51c3edc5825332fd6d88bc1988faf0a48872","schema_version":"1.0","event_id":"sha256:72a0cff6811ea1b05c742468858e51c3edc5825332fd6d88bc1988faf0a48872"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:4S3PHV6E2BBRDSBRCBJ7KZULJL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Non-Parametric Adaptation for Neural Machine Translation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.CL","authors_text":"Ankur Bapna, Orhan Firat","submitted_at":"2019-02-28T20:33:00Z","abstract_excerpt":"Neural Networks trained with gradient descent are known to be susceptible to catastrophic forgetting caused by parameter shift during the training process. In the context of Neural Machine Translation (NMT) this results in poor performance on heterogeneous datasets and on sub-tasks like rare phrase translation. On the other hand, non-parametric approaches are immune to forgetting, perfectly complementing the generalization ability of NMT. However, attempts to combine non-parametric or retrieval based approaches with NMT have only been successful on narrow domains, possibly due to over-reliance"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.00058","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":"2026-05-17T23:42:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Vf/1vT7WYVZqikQRp4gqNWydRVM9z+X9zNltk3Yfo/daqzEtOVJHhwIHHQrVNE+j+CMXPVD5VcVM7E2hPIoGCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T15:57:37.644574Z"},"content_sha256":"0b633a2a482ff36f3a3dcb377c0222b0d3f123e6e897a4d51fe14f3526ae499a","schema_version":"1.0","event_id":"sha256:0b633a2a482ff36f3a3dcb377c0222b0d3f123e6e897a4d51fe14f3526ae499a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4S3PHV6E2BBRDSBRCBJ7KZULJL/bundle.json","state_url":"https://pith.science/pith/4S3PHV6E2BBRDSBRCBJ7KZULJL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4S3PHV6E2BBRDSBRCBJ7KZULJL/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":"2026-08-16T15:57:37Z","links":{"resolver":"https://pith.science/pith/4S3PHV6E2BBRDSBRCBJ7KZULJL","bundle":"https://pith.science/pith/4S3PHV6E2BBRDSBRCBJ7KZULJL/bundle.json","state":"https://pith.science/pith/4S3PHV6E2BBRDSBRCBJ7KZULJL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4S3PHV6E2BBRDSBRCBJ7KZULJL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:4S3PHV6E2BBRDSBRCBJ7KZULJL","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":"e1165898da9f84edc12c0dca95ea6c141d61c27b94de7f94398d744a9d20bd25","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-02-28T20:33:00Z","title_canon_sha256":"d8ac4982e308af57e6cef6859d526aa912ec1f2f82d0c11075c54dbd41f795aa"},"schema_version":"1.0","source":{"id":"1903.00058","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.00058","created_at":"2026-05-17T23:42:58Z"},{"alias_kind":"arxiv_version","alias_value":"1903.00058v2","created_at":"2026-05-17T23:42:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.00058","created_at":"2026-05-17T23:42:58Z"},{"alias_kind":"pith_short_12","alias_value":"4S3PHV6E2BBR","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4S3PHV6E2BBRDSBR","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4S3PHV6E","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:0b633a2a482ff36f3a3dcb377c0222b0d3f123e6e897a4d51fe14f3526ae499a","target":"graph","created_at":"2026-05-17T23:42:58Z","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":"Neural Networks trained with gradient descent are known to be susceptible to catastrophic forgetting caused by parameter shift during the training process. In the context of Neural Machine Translation (NMT) this results in poor performance on heterogeneous datasets and on sub-tasks like rare phrase translation. On the other hand, non-parametric approaches are immune to forgetting, perfectly complementing the generalization ability of NMT. However, attempts to combine non-parametric or retrieval based approaches with NMT have only been successful on narrow domains, possibly due to over-reliance","authors_text":"Ankur Bapna, Orhan Firat","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-02-28T20:33:00Z","title":"Non-Parametric Adaptation for Neural Machine Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.00058","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":"sha256:72a0cff6811ea1b05c742468858e51c3edc5825332fd6d88bc1988faf0a48872","target":"record","created_at":"2026-05-17T23:42:58Z","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":"e1165898da9f84edc12c0dca95ea6c141d61c27b94de7f94398d744a9d20bd25","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-02-28T20:33:00Z","title_canon_sha256":"d8ac4982e308af57e6cef6859d526aa912ec1f2f82d0c11075c54dbd41f795aa"},"schema_version":"1.0","source":{"id":"1903.00058","kind":"arxiv","version":2}},"canonical_sha256":"e4b6f3d7c4d04311c8311053f5668b4afd063655fdfebe8c3149403255d5f1f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e4b6f3d7c4d04311c8311053f5668b4afd063655fdfebe8c3149403255d5f1f3","first_computed_at":"2026-05-17T23:42:58.440266Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:42:58.440266Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0+TSuWzJjaIv3wTvBUd1LZEhqDzpsxF9gjaGlL+H8bdZ2Lazq8BWj80jAfq5Vb+d87xRdKgKqtnQr5MXBSCwCg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:42:58.440793Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.00058","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:72a0cff6811ea1b05c742468858e51c3edc5825332fd6d88bc1988faf0a48872","sha256:0b633a2a482ff36f3a3dcb377c0222b0d3f123e6e897a4d51fe14f3526ae499a"],"state_sha256":"9d691f1c4cb01856cb0bacc2ea001694e92ac806ab734ce61e7ff160760b4cf9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aSchX2h+3ZnS3HOeDs9SjsFtm8GMP+OihiRugTJuUse4rIA3Xm8fhqPj4PMqlxs3yS+LvgA8JRdtsfAX/jSbBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T15:57:37.650007Z","bundle_sha256":"c4ab934a7fe845a38b43b732c3ebe4dd17f073a1a900e429be818a16a8c671a1"}}