{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:NDSW2WCJST6PVM5LLWXF7QYSUR","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":"34a4d776ae59b51722bcfb56534458f0db5425ea79a9bcb1dec3c5a3ec114cdf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-09-25T14:33:47Z","title_canon_sha256":"d92523cefbdd0fb5caa7be380c7ea077d0c46f91c6c7d7f0325f4d592b02c55d"},"schema_version":"1.0","source":{"id":"2309.14174","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.14174","created_at":"2026-07-05T06:54:02Z"},{"alias_kind":"arxiv_version","alias_value":"2309.14174v1","created_at":"2026-07-05T06:54:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.14174","created_at":"2026-07-05T06:54:02Z"},{"alias_kind":"pith_short_12","alias_value":"NDSW2WCJST6P","created_at":"2026-07-05T06:54:02Z"},{"alias_kind":"pith_short_16","alias_value":"NDSW2WCJST6PVM5L","created_at":"2026-07-05T06:54:02Z"},{"alias_kind":"pith_short_8","alias_value":"NDSW2WCJ","created_at":"2026-07-05T06:54:02Z"}],"graph_snapshots":[{"event_id":"sha256:f8ce0e865cb9dcf591c0fc01845ba97cb842f1bfa1a18b7435d8f154f858e744","target":"graph","created_at":"2026-07-05T06:54:02Z","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/2309.14174/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Document-level Neural Machine Translation (DocNMT) has been proven crucial for handling discourse phenomena by introducing document-level context information. One of the most important directions is to input the whole document directly to the standard Transformer model. In this case, efficiency becomes a critical concern due to the quadratic complexity of the attention module. Existing studies either focus on the encoder part, which cannot be deployed on sequence-to-sequence generation tasks, e.g., Machine Translation (MT), or suffer from a significant performance drop. In this work, we keep t","authors_text":"Mingxuan Wang, Shanbo Cheng, Shujian Huang, Zewei Sun, Zihan Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-09-25T14:33:47Z","title":"Only 5\\% Attention Is All You Need: Efficient Long-range Document-level Neural Machine Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.14174","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":"sha256:6a94f0055a40459adb49c90ab49e3223eb7ed49add55a112e126fc149a2cdf6c","target":"record","created_at":"2026-07-05T06:54:02Z","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":"34a4d776ae59b51722bcfb56534458f0db5425ea79a9bcb1dec3c5a3ec114cdf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-09-25T14:33:47Z","title_canon_sha256":"d92523cefbdd0fb5caa7be380c7ea077d0c46f91c6c7d7f0325f4d592b02c55d"},"schema_version":"1.0","source":{"id":"2309.14174","kind":"arxiv","version":1}},"canonical_sha256":"68e56d584994fcfab3ab5dae5fc312a46800277a0f9e5b91dc3a7bb694f0837c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"68e56d584994fcfab3ab5dae5fc312a46800277a0f9e5b91dc3a7bb694f0837c","first_computed_at":"2026-07-05T06:54:02.481572Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:54:02.481572Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7c2C0yiau2VnExjvyfxXZPl5R6EmFUaAh4IFz0zBFOtG+9BwBSyIBCNEZ3nfhu1mO5V7wUt1Lw1IrNLGA0ujAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:54:02.481994Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.14174","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6a94f0055a40459adb49c90ab49e3223eb7ed49add55a112e126fc149a2cdf6c","sha256:f8ce0e865cb9dcf591c0fc01845ba97cb842f1bfa1a18b7435d8f154f858e744"],"state_sha256":"28e5349494a94f714c50f5dca8b60f41ca00ba675bcbab52e8de7e2b87159b62"}