{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:WDJICMGHJFBQ6EEQL5UPQLTX6H","short_pith_number":"pith:WDJICMGH","canonical_record":{"source":{"id":"2501.00334","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-31T08:11:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e5775ed0c937e2ad263bf0811c2a18ba02efd1b4c916937cbb71e2944cd93b09","abstract_canon_sha256":"d06a5381cfd92bc583018f6cba9c693e48cdf599bf66ab34634be7a30ce43be8"},"schema_version":"1.0"},"canonical_sha256":"b0d28130c749430f10905f68f82e77f1eeffbf57132e07052b51d1220dafdbd4","source":{"kind":"arxiv","id":"2501.00334","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.00334","created_at":"2026-07-05T09:55:43Z"},{"alias_kind":"arxiv_version","alias_value":"2501.00334v1","created_at":"2026-07-05T09:55:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.00334","created_at":"2026-07-05T09:55:43Z"},{"alias_kind":"pith_short_12","alias_value":"WDJICMGHJFBQ","created_at":"2026-07-05T09:55:43Z"},{"alias_kind":"pith_short_16","alias_value":"WDJICMGHJFBQ6EEQ","created_at":"2026-07-05T09:55:43Z"},{"alias_kind":"pith_short_8","alias_value":"WDJICMGH","created_at":"2026-07-05T09:55:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:WDJICMGHJFBQ6EEQL5UPQLTX6H","target":"record","payload":{"canonical_record":{"source":{"id":"2501.00334","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-31T08:11:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e5775ed0c937e2ad263bf0811c2a18ba02efd1b4c916937cbb71e2944cd93b09","abstract_canon_sha256":"d06a5381cfd92bc583018f6cba9c693e48cdf599bf66ab34634be7a30ce43be8"},"schema_version":"1.0"},"canonical_sha256":"b0d28130c749430f10905f68f82e77f1eeffbf57132e07052b51d1220dafdbd4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:55:43.186260Z","signature_b64":"Hopl3e60DAeYk0I0LcEmuA/X7tPcp7wO1zXkNHzkWacP0VMsiOUe0tmzBKTVLYU/aUdSmzaHm4TcfQ65fFqxAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b0d28130c749430f10905f68f82e77f1eeffbf57132e07052b51d1220dafdbd4","last_reissued_at":"2026-07-05T09:55:43.185762Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:55:43.185762Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.00334","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":"2026-07-05T09:55:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x/16yiWr6gDd6fjbACLvQjzQSQ7R5yJe983YTxAnLv96vSqt3f3Q39sd3wSAWzu35J6r3NHd1QfLAuoSEKCqDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T22:20:57.141576Z"},"content_sha256":"a11069255b533ac929dcddab0696f2f01d257250ef3533ec224a2eb6a22ab54b","schema_version":"1.0","event_id":"sha256:a11069255b533ac929dcddab0696f2f01d257250ef3533ec224a2eb6a22ab54b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:WDJICMGHJFBQ6EEQL5UPQLTX6H","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Loss-Aware Curriculum Learning for Chinese Grammatical Error Correction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Ding Zhang, Hai-Tao Zheng, Haiye Lin, Hao Zhang, Lichen Bai, Xin Su, Yangning Li, Yinghui Li, Zifei Shan","submitted_at":"2024-12-31T08:11:49Z","abstract_excerpt":"Chinese grammatical error correction (CGEC) aims to detect and correct errors in the input Chinese sentences. Recently, Pre-trained Language Models (PLMS) have been employed to improve the performance. However, current approaches ignore that correction difficulty varies across different instances and treat these samples equally, enhancing the challenge of model learning. To address this problem, we propose a multi-granularity Curriculum Learning (CL) framework. Specifically, we first calculate the correction difficulty of these samples and feed them into the model from easy to hard batch by ba"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.00334","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/2501.00334/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":"2026-07-05T09:55:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nngOuR7bWso9CzKVKTS0ZniL03f29WAAn5OiCbLuN0vB77N/D7UwwcbD7o/nNBqR5FK0RPtL+z93xFiRzAxPAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T22:20:57.142285Z"},"content_sha256":"e535920e7f2b079f702320ffecb85b266c6560565ec05112d9fa808fb2dcf8f9","schema_version":"1.0","event_id":"sha256:e535920e7f2b079f702320ffecb85b266c6560565ec05112d9fa808fb2dcf8f9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WDJICMGHJFBQ6EEQL5UPQLTX6H/bundle.json","state_url":"https://pith.science/pith/WDJICMGHJFBQ6EEQL5UPQLTX6H/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WDJICMGHJFBQ6EEQL5UPQLTX6H/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":"2026-08-12T22:20:57Z","links":{"resolver":"https://pith.science/pith/WDJICMGHJFBQ6EEQL5UPQLTX6H","bundle":"https://pith.science/pith/WDJICMGHJFBQ6EEQL5UPQLTX6H/bundle.json","state":"https://pith.science/pith/WDJICMGHJFBQ6EEQL5UPQLTX6H/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WDJICMGHJFBQ6EEQL5UPQLTX6H/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:WDJICMGHJFBQ6EEQL5UPQLTX6H","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":"d06a5381cfd92bc583018f6cba9c693e48cdf599bf66ab34634be7a30ce43be8","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-31T08:11:49Z","title_canon_sha256":"e5775ed0c937e2ad263bf0811c2a18ba02efd1b4c916937cbb71e2944cd93b09"},"schema_version":"1.0","source":{"id":"2501.00334","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.00334","created_at":"2026-07-05T09:55:43Z"},{"alias_kind":"arxiv_version","alias_value":"2501.00334v1","created_at":"2026-07-05T09:55:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.00334","created_at":"2026-07-05T09:55:43Z"},{"alias_kind":"pith_short_12","alias_value":"WDJICMGHJFBQ","created_at":"2026-07-05T09:55:43Z"},{"alias_kind":"pith_short_16","alias_value":"WDJICMGHJFBQ6EEQ","created_at":"2026-07-05T09:55:43Z"},{"alias_kind":"pith_short_8","alias_value":"WDJICMGH","created_at":"2026-07-05T09:55:43Z"}],"graph_snapshots":[{"event_id":"sha256:e535920e7f2b079f702320ffecb85b266c6560565ec05112d9fa808fb2dcf8f9","target":"graph","created_at":"2026-07-05T09:55:43Z","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/2501.00334/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Chinese grammatical error correction (CGEC) aims to detect and correct errors in the input Chinese sentences. Recently, Pre-trained Language Models (PLMS) have been employed to improve the performance. However, current approaches ignore that correction difficulty varies across different instances and treat these samples equally, enhancing the challenge of model learning. To address this problem, we propose a multi-granularity Curriculum Learning (CL) framework. Specifically, we first calculate the correction difficulty of these samples and feed them into the model from easy to hard batch by ba","authors_text":"Ding Zhang, Hai-Tao Zheng, Haiye Lin, Hao Zhang, Lichen Bai, Xin Su, Yangning Li, Yinghui Li, Zifei Shan","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-31T08:11:49Z","title":"Loss-Aware Curriculum Learning for Chinese Grammatical Error Correction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.00334","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:a11069255b533ac929dcddab0696f2f01d257250ef3533ec224a2eb6a22ab54b","target":"record","created_at":"2026-07-05T09:55:43Z","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":"d06a5381cfd92bc583018f6cba9c693e48cdf599bf66ab34634be7a30ce43be8","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-31T08:11:49Z","title_canon_sha256":"e5775ed0c937e2ad263bf0811c2a18ba02efd1b4c916937cbb71e2944cd93b09"},"schema_version":"1.0","source":{"id":"2501.00334","kind":"arxiv","version":1}},"canonical_sha256":"b0d28130c749430f10905f68f82e77f1eeffbf57132e07052b51d1220dafdbd4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b0d28130c749430f10905f68f82e77f1eeffbf57132e07052b51d1220dafdbd4","first_computed_at":"2026-07-05T09:55:43.185762Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:55:43.185762Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Hopl3e60DAeYk0I0LcEmuA/X7tPcp7wO1zXkNHzkWacP0VMsiOUe0tmzBKTVLYU/aUdSmzaHm4TcfQ65fFqxAw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:55:43.186260Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.00334","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a11069255b533ac929dcddab0696f2f01d257250ef3533ec224a2eb6a22ab54b","sha256:e535920e7f2b079f702320ffecb85b266c6560565ec05112d9fa808fb2dcf8f9"],"state_sha256":"596122ddce8b529780f2a22923349cbce3bd093e1d3b0918e1fc90b1867a34ce"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i4B9VFte5wCCcKTmZx35u5/MN9XHPTc3QvVOxPmhqRn/5BiRFQWplEdoGuU5jAoyRt3qG3CX7SwZ3ESLiwczBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T22:20:57.150462Z","bundle_sha256":"741717c74c7c46c2d4a16c5e5d5760b5f1f3f78655964207f4eafb75c88ea7a6"}}