{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:ZP7EHJJV2OJWW5XTFHJNKIGOHR","short_pith_number":"pith:ZP7EHJJV","canonical_record":{"source":{"id":"2301.06825","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-01-17T12:07:13Z","cross_cats_sorted":[],"title_canon_sha256":"e1f4d1474c5f12c0b45146ca5b0045cf20cf65dfb33f2c3ed87c3bca3e143208","abstract_canon_sha256":"84ecd1871f1554f52885946e96356ea12b8cd22e8913783e0d500d2d5100d5ae"},"schema_version":"1.0"},"canonical_sha256":"cbfe43a535d3936b76f329d2d520ce3c5feb130b20f924a5fcdac66ab4ebe4b6","source":{"kind":"arxiv","id":"2301.06825","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.06825","created_at":"2026-07-05T06:02:31Z"},{"alias_kind":"arxiv_version","alias_value":"2301.06825v1","created_at":"2026-07-05T06:02:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.06825","created_at":"2026-07-05T06:02:31Z"},{"alias_kind":"pith_short_12","alias_value":"ZP7EHJJV2OJW","created_at":"2026-07-05T06:02:31Z"},{"alias_kind":"pith_short_16","alias_value":"ZP7EHJJV2OJWW5XT","created_at":"2026-07-05T06:02:31Z"},{"alias_kind":"pith_short_8","alias_value":"ZP7EHJJV","created_at":"2026-07-05T06:02:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:ZP7EHJJV2OJWW5XTFHJNKIGOHR","target":"record","payload":{"canonical_record":{"source":{"id":"2301.06825","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-01-17T12:07:13Z","cross_cats_sorted":[],"title_canon_sha256":"e1f4d1474c5f12c0b45146ca5b0045cf20cf65dfb33f2c3ed87c3bca3e143208","abstract_canon_sha256":"84ecd1871f1554f52885946e96356ea12b8cd22e8913783e0d500d2d5100d5ae"},"schema_version":"1.0"},"canonical_sha256":"cbfe43a535d3936b76f329d2d520ce3c5feb130b20f924a5fcdac66ab4ebe4b6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:02:31.978937Z","signature_b64":"2FNf6E8mQQd3iGEsJOmDPui8FPmGHf7KWrH7O/wrLWAZnJu4yfh1CHQQU43tNVQwHv8mSEFCEUzjIRXAlNJ6Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cbfe43a535d3936b76f329d2d520ce3c5feb130b20f924a5fcdac66ab4ebe4b6","last_reissued_at":"2026-07-05T06:02:31.978511Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:02:31.978511Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2301.06825","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":"2026-07-05T06:02:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GfnzsOU1cKXX/w0iAdNnWalw24NTMplJo55yr+Ia8DVE9eJA1KKSCu8ebmRgUT9WEpTadedUXlNrwSFrih5/Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T05:22:20.930213Z"},"content_sha256":"835408b2d211e439f06549449e2cd7bf9190910b99d991a2b76be3e86f7ff72e","schema_version":"1.0","event_id":"sha256:835408b2d211e439f06549449e2cd7bf9190910b99d991a2b76be3e86f7ff72e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:ZP7EHJJV2OJWW5XTFHJNKIGOHR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"HanoiT: Enhancing Context-aware Translation via Selective Context","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dongdong Zhang, Furu Wei, Haoyang Huang, Hongcheng Guo, Jian Yang, Liqun Yang, Shuming Ma, Yutao Zeng, Yuwei Yin, Zhoujun Li","submitted_at":"2023-01-17T12:07:13Z","abstract_excerpt":"Context-aware neural machine translation aims to use the document-level context to improve translation quality. However, not all words in the context are helpful. The irrelevant or trivial words may bring some noise and distract the model from learning the relationship between the current sentence and the auxiliary context. To mitigate this problem, we propose a novel end-to-end encoder-decoder model with a layer-wise selection mechanism to sift and refine the long document context. To verify the effectiveness of our method, extensive experiments and extra quantitative analysis are conducted o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.06825","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/2301.06825/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":"2026-07-05T06:02:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FYSgn2h0ei9QKgte40M0MXKTOeQZHLUYn4bppw/bi5qbwdbIC0WJ7r1ribjX7OdjNy++MyHH23ldeK3u81vqBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T05:22:20.930794Z"},"content_sha256":"560d7b5c64500a99cc601c0314a271ab3493d7d1e5d9fea79419e6020559af99","schema_version":"1.0","event_id":"sha256:560d7b5c64500a99cc601c0314a271ab3493d7d1e5d9fea79419e6020559af99"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZP7EHJJV2OJWW5XTFHJNKIGOHR/bundle.json","state_url":"https://pith.science/pith/ZP7EHJJV2OJWW5XTFHJNKIGOHR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZP7EHJJV2OJWW5XTFHJNKIGOHR/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":"2026-08-21T05:22:20Z","links":{"resolver":"https://pith.science/pith/ZP7EHJJV2OJWW5XTFHJNKIGOHR","bundle":"https://pith.science/pith/ZP7EHJJV2OJWW5XTFHJNKIGOHR/bundle.json","state":"https://pith.science/pith/ZP7EHJJV2OJWW5XTFHJNKIGOHR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZP7EHJJV2OJWW5XTFHJNKIGOHR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:ZP7EHJJV2OJWW5XTFHJNKIGOHR","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":"84ecd1871f1554f52885946e96356ea12b8cd22e8913783e0d500d2d5100d5ae","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-01-17T12:07:13Z","title_canon_sha256":"e1f4d1474c5f12c0b45146ca5b0045cf20cf65dfb33f2c3ed87c3bca3e143208"},"schema_version":"1.0","source":{"id":"2301.06825","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.06825","created_at":"2026-07-05T06:02:31Z"},{"alias_kind":"arxiv_version","alias_value":"2301.06825v1","created_at":"2026-07-05T06:02:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.06825","created_at":"2026-07-05T06:02:31Z"},{"alias_kind":"pith_short_12","alias_value":"ZP7EHJJV2OJW","created_at":"2026-07-05T06:02:31Z"},{"alias_kind":"pith_short_16","alias_value":"ZP7EHJJV2OJWW5XT","created_at":"2026-07-05T06:02:31Z"},{"alias_kind":"pith_short_8","alias_value":"ZP7EHJJV","created_at":"2026-07-05T06:02:31Z"}],"graph_snapshots":[{"event_id":"sha256:560d7b5c64500a99cc601c0314a271ab3493d7d1e5d9fea79419e6020559af99","target":"graph","created_at":"2026-07-05T06:02:31Z","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/2301.06825/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Context-aware neural machine translation aims to use the document-level context to improve translation quality. However, not all words in the context are helpful. The irrelevant or trivial words may bring some noise and distract the model from learning the relationship between the current sentence and the auxiliary context. To mitigate this problem, we propose a novel end-to-end encoder-decoder model with a layer-wise selection mechanism to sift and refine the long document context. To verify the effectiveness of our method, extensive experiments and extra quantitative analysis are conducted o","authors_text":"Dongdong Zhang, Furu Wei, Haoyang Huang, Hongcheng Guo, Jian Yang, Liqun Yang, Shuming Ma, Yutao Zeng, Yuwei Yin, Zhoujun Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-01-17T12:07:13Z","title":"HanoiT: Enhancing Context-aware Translation via Selective Context"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.06825","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":"sha256:835408b2d211e439f06549449e2cd7bf9190910b99d991a2b76be3e86f7ff72e","target":"record","created_at":"2026-07-05T06:02:31Z","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":"84ecd1871f1554f52885946e96356ea12b8cd22e8913783e0d500d2d5100d5ae","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-01-17T12:07:13Z","title_canon_sha256":"e1f4d1474c5f12c0b45146ca5b0045cf20cf65dfb33f2c3ed87c3bca3e143208"},"schema_version":"1.0","source":{"id":"2301.06825","kind":"arxiv","version":1}},"canonical_sha256":"cbfe43a535d3936b76f329d2d520ce3c5feb130b20f924a5fcdac66ab4ebe4b6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cbfe43a535d3936b76f329d2d520ce3c5feb130b20f924a5fcdac66ab4ebe4b6","first_computed_at":"2026-07-05T06:02:31.978511Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:02:31.978511Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2FNf6E8mQQd3iGEsJOmDPui8FPmGHf7KWrH7O/wrLWAZnJu4yfh1CHQQU43tNVQwHv8mSEFCEUzjIRXAlNJ6Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T06:02:31.978937Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.06825","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:835408b2d211e439f06549449e2cd7bf9190910b99d991a2b76be3e86f7ff72e","sha256:560d7b5c64500a99cc601c0314a271ab3493d7d1e5d9fea79419e6020559af99"],"state_sha256":"e2700b6bc0bb95f30e9c45cde3007a1f5d997c0703f3eda7cb7d67f61f2b76d9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nPMhdiIKBCOHwFH0X3TOZ9+hlSuMdeXp/BBRJk474JQ2RXsstLypv7gmy+nKa3sQo/crXlZ07LkQMjItO9SABg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T05:22:20.934730Z","bundle_sha256":"190a5f5036b79ade53667c617b203961caa5d1feefa34ab57d3e4d1c9db9bc83"}}