{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:K3CSNHZNG3T4CFZRXK3OWELUML","short_pith_number":"pith:K3CSNHZN","canonical_record":{"source":{"id":"2406.01198","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-03T10:59:50Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"211c0aec88e5055e9d758c744c80331af2a26350ef6167b59ce9b6bd2765e7ef","abstract_canon_sha256":"5da99f11b6544e3e3710da890baf60271fad2d07623b732381cba1011b9cc782"},"schema_version":"1.0"},"canonical_sha256":"56c5269f2d36e7c11731bab6eb117462c4e75e99814d3c501f2a05fa131eb4f7","source":{"kind":"arxiv","id":"2406.01198","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.01198","created_at":"2026-07-05T08:26:36Z"},{"alias_kind":"arxiv_version","alias_value":"2406.01198v1","created_at":"2026-07-05T08:26:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.01198","created_at":"2026-07-05T08:26:36Z"},{"alias_kind":"pith_short_12","alias_value":"K3CSNHZNG3T4","created_at":"2026-07-05T08:26:36Z"},{"alias_kind":"pith_short_16","alias_value":"K3CSNHZNG3T4CFZR","created_at":"2026-07-05T08:26:36Z"},{"alias_kind":"pith_short_8","alias_value":"K3CSNHZN","created_at":"2026-07-05T08:26:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:K3CSNHZNG3T4CFZRXK3OWELUML","target":"record","payload":{"canonical_record":{"source":{"id":"2406.01198","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-03T10:59:50Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"211c0aec88e5055e9d758c744c80331af2a26350ef6167b59ce9b6bd2765e7ef","abstract_canon_sha256":"5da99f11b6544e3e3710da890baf60271fad2d07623b732381cba1011b9cc782"},"schema_version":"1.0"},"canonical_sha256":"56c5269f2d36e7c11731bab6eb117462c4e75e99814d3c501f2a05fa131eb4f7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:26:36.703988Z","signature_b64":"CFmwiIKBOW/vLnzxEUAydJFFhHN6UOx8EMPq1Gt1EIkphkXyf1llz50cxi6fPOcLlWHJ/Zm42HHMWG0KZ1ZDAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"56c5269f2d36e7c11731bab6eb117462c4e75e99814d3c501f2a05fa131eb4f7","last_reissued_at":"2026-07-05T08:26:36.703527Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:26:36.703527Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.01198","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":"2026-07-05T08:26:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8JMRp0ovIlMW7pZYiWHa2gCeUCneToaigm5plR8apU72jh550fAZdCk+VH0ND3xB1O1H/DvtwKKcPr3O0ObxDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T14:00:38.906461Z"},"content_sha256":"d967f88c04b410feae743d2e0323beed11d20e745361a7ad264c526faa664fc7","schema_version":"1.0","event_id":"sha256:d967f88c04b410feae743d2e0323beed11d20e745361a7ad264c526faa664fc7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:K3CSNHZNG3T4CFZRXK3OWELUML","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Automatic Essay Multi-dimensional Scoring with Fine-tuning and Multiple Regression","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Kun Sun, Rong Wang","submitted_at":"2024-06-03T10:59:50Z","abstract_excerpt":"Automated essay scoring (AES) involves predicting a score that reflects the writing quality of an essay. Most existing AES systems produce only a single overall score. However, users and L2 learners expect scores across different dimensions (e.g., vocabulary, grammar, coherence) for English essays in real-world applications. To address this need, we have developed two models that automatically score English essays across multiple dimensions by employing fine-tuning and other strategies on two large datasets. The results demonstrate that our systems achieve impressive performance in evaluation "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.01198","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/2406.01198/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":"2026-07-05T08:26:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P8n86B6Rt361KbSG239iBk7r+lWCrxOi+4TB+l567zQE35TGQxbcxBwytatUTwrozAogzm7LWv0gncw1ZowDDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T14:00:38.907405Z"},"content_sha256":"2b5d8f7092e4b36c9a89098c6693d223f3c1005b46e8de1342167e1bff1534c8","schema_version":"1.0","event_id":"sha256:2b5d8f7092e4b36c9a89098c6693d223f3c1005b46e8de1342167e1bff1534c8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/K3CSNHZNG3T4CFZRXK3OWELUML/bundle.json","state_url":"https://pith.science/pith/K3CSNHZNG3T4CFZRXK3OWELUML/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/K3CSNHZNG3T4CFZRXK3OWELUML/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":"2026-08-13T14:00:38Z","links":{"resolver":"https://pith.science/pith/K3CSNHZNG3T4CFZRXK3OWELUML","bundle":"https://pith.science/pith/K3CSNHZNG3T4CFZRXK3OWELUML/bundle.json","state":"https://pith.science/pith/K3CSNHZNG3T4CFZRXK3OWELUML/state.json","well_known_bundle":"https://pith.science/.well-known/pith/K3CSNHZNG3T4CFZRXK3OWELUML/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:K3CSNHZNG3T4CFZRXK3OWELUML","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":"5da99f11b6544e3e3710da890baf60271fad2d07623b732381cba1011b9cc782","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-03T10:59:50Z","title_canon_sha256":"211c0aec88e5055e9d758c744c80331af2a26350ef6167b59ce9b6bd2765e7ef"},"schema_version":"1.0","source":{"id":"2406.01198","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.01198","created_at":"2026-07-05T08:26:36Z"},{"alias_kind":"arxiv_version","alias_value":"2406.01198v1","created_at":"2026-07-05T08:26:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.01198","created_at":"2026-07-05T08:26:36Z"},{"alias_kind":"pith_short_12","alias_value":"K3CSNHZNG3T4","created_at":"2026-07-05T08:26:36Z"},{"alias_kind":"pith_short_16","alias_value":"K3CSNHZNG3T4CFZR","created_at":"2026-07-05T08:26:36Z"},{"alias_kind":"pith_short_8","alias_value":"K3CSNHZN","created_at":"2026-07-05T08:26:36Z"}],"graph_snapshots":[{"event_id":"sha256:2b5d8f7092e4b36c9a89098c6693d223f3c1005b46e8de1342167e1bff1534c8","target":"graph","created_at":"2026-07-05T08:26:36Z","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/2406.01198/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automated essay scoring (AES) involves predicting a score that reflects the writing quality of an essay. Most existing AES systems produce only a single overall score. However, users and L2 learners expect scores across different dimensions (e.g., vocabulary, grammar, coherence) for English essays in real-world applications. To address this need, we have developed two models that automatically score English essays across multiple dimensions by employing fine-tuning and other strategies on two large datasets. The results demonstrate that our systems achieve impressive performance in evaluation ","authors_text":"Kun Sun, Rong Wang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-03T10:59:50Z","title":"Automatic Essay Multi-dimensional Scoring with Fine-tuning and Multiple Regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.01198","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:d967f88c04b410feae743d2e0323beed11d20e745361a7ad264c526faa664fc7","target":"record","created_at":"2026-07-05T08:26:36Z","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":"5da99f11b6544e3e3710da890baf60271fad2d07623b732381cba1011b9cc782","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-03T10:59:50Z","title_canon_sha256":"211c0aec88e5055e9d758c744c80331af2a26350ef6167b59ce9b6bd2765e7ef"},"schema_version":"1.0","source":{"id":"2406.01198","kind":"arxiv","version":1}},"canonical_sha256":"56c5269f2d36e7c11731bab6eb117462c4e75e99814d3c501f2a05fa131eb4f7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"56c5269f2d36e7c11731bab6eb117462c4e75e99814d3c501f2a05fa131eb4f7","first_computed_at":"2026-07-05T08:26:36.703527Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:26:36.703527Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CFmwiIKBOW/vLnzxEUAydJFFhHN6UOx8EMPq1Gt1EIkphkXyf1llz50cxi6fPOcLlWHJ/Zm42HHMWG0KZ1ZDAA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:26:36.703988Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.01198","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d967f88c04b410feae743d2e0323beed11d20e745361a7ad264c526faa664fc7","sha256:2b5d8f7092e4b36c9a89098c6693d223f3c1005b46e8de1342167e1bff1534c8"],"state_sha256":"dd46b34193ca3895d275989bebf4cd496712a96968dd768cb6a8608b49dd566c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n84/K9AnNUDyuzrgjbbcEii/wipiYSKTaQ9QfUwBzVnbNttrGrR/e3SZH01qxCWtSjJYY2ZjhShebOfnM9HdAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T14:00:38.915784Z","bundle_sha256":"1689eaa60ab1543738aa0033c8081351a3de76c6ca68da8b27a4e5ed0103acc2"}}