{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QLM66K5VP35DNK7DTJB4F6W5CI","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":"9a46f338b4497646fde8a3c8945a97012cf878d4dbf47f79f8579e99321b50d2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-29T15:07:19Z","title_canon_sha256":"0ca69d553cc7df15b2352bbd2a0684a6e15ca6e3ebbb7ca0bc43298f3519aa0d"},"schema_version":"1.0","source":{"id":"2407.20083","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.20083","created_at":"2026-07-05T08:49:48Z"},{"alias_kind":"arxiv_version","alias_value":"2407.20083v1","created_at":"2026-07-05T08:49:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.20083","created_at":"2026-07-05T08:49:48Z"},{"alias_kind":"pith_short_12","alias_value":"QLM66K5VP35D","created_at":"2026-07-05T08:49:48Z"},{"alias_kind":"pith_short_16","alias_value":"QLM66K5VP35DNK7D","created_at":"2026-07-05T08:49:48Z"},{"alias_kind":"pith_short_8","alias_value":"QLM66K5V","created_at":"2026-07-05T08:49:48Z"}],"graph_snapshots":[{"event_id":"sha256:b7929e06cd00fb3acda0d07710976465cb25b547d5d206269fe392b5b106f5c2","target":"graph","created_at":"2026-07-05T08:49:48Z","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/2407.20083/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Word-level AutoCompletion(WLAC) is a rewarding yet challenging task in Computer-aided Translation. Existing work addresses this task through a classification model based on a neural network that maps the hidden vector of the input context into its corresponding label (i.e., the candidate target word is treated as a label). Since the context hidden vector itself does not take the label into account and it is projected to the label through a linear classifier, the model can not sufficiently leverage valuable information from the source sentence as verified in our experiments, which eventually hi","authors_text":"Cheng Yang, Guoping Huang, Lemao Liu, Mingming Yang, Mo Yu, Shuming Shi, Siheng Li, Yujiu Yang, Zhirui Zhang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-29T15:07:19Z","title":"An Energy-based Model for Word-level AutoCompletion in Computer-aided Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.20083","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":"sha256:9c96cabbf9f2dc581aea2e8501b700fe7da84cbcc05c48e79995bab2ba1e9b0b","target":"record","created_at":"2026-07-05T08:49:48Z","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":"9a46f338b4497646fde8a3c8945a97012cf878d4dbf47f79f8579e99321b50d2","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-29T15:07:19Z","title_canon_sha256":"0ca69d553cc7df15b2352bbd2a0684a6e15ca6e3ebbb7ca0bc43298f3519aa0d"},"schema_version":"1.0","source":{"id":"2407.20083","kind":"arxiv","version":1}},"canonical_sha256":"82d9ef2bb57efa36abe39a43c2fadd1222e9f439611aa7afe27c0e845ad7b89f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"82d9ef2bb57efa36abe39a43c2fadd1222e9f439611aa7afe27c0e845ad7b89f","first_computed_at":"2026-07-05T08:49:48.687912Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:49:48.687912Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"W0rL9vlsShQHDHtzuDqIe0HWxNR+0djJW6y+T6bbt9OMBBS9jGJgfs0eH7f1TMuVN2EWNGIACqDCmebvmXibAA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:49:48.688277Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.20083","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9c96cabbf9f2dc581aea2e8501b700fe7da84cbcc05c48e79995bab2ba1e9b0b","sha256:b7929e06cd00fb3acda0d07710976465cb25b547d5d206269fe392b5b106f5c2"],"state_sha256":"21ae78bdda9bf6952b36250a9917da569dd39412de77d2dc88805637abb8cfc9"}