{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:ZN7PMRYFABJCKJWUGLHYASIXH2","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":"54c50eb507b1bc522a0599222ecfefbbf24175e74ecd8e5adfb97b4d7e3cc758","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-10-12T03:20:43Z","title_canon_sha256":"fcd9727c49dd1403e359b53a61bbc0325a1a3ed14622037cf176aa5b9b00e27c"},"schema_version":"1.0","source":{"id":"2310.08008","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.08008","created_at":"2026-07-05T07:22:24Z"},{"alias_kind":"arxiv_version","alias_value":"2310.08008v4","created_at":"2026-07-05T07:22:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.08008","created_at":"2026-07-05T07:22:24Z"},{"alias_kind":"pith_short_12","alias_value":"ZN7PMRYFABJC","created_at":"2026-07-05T07:22:24Z"},{"alias_kind":"pith_short_16","alias_value":"ZN7PMRYFABJCKJWU","created_at":"2026-07-05T07:22:24Z"},{"alias_kind":"pith_short_8","alias_value":"ZN7PMRYF","created_at":"2026-07-05T07:22:24Z"}],"graph_snapshots":[{"event_id":"sha256:ac1b1421c8049a789cb5ae00084294ceca4dde96f0c062ddf5f7fd93f5fa5fbc","target":"graph","created_at":"2026-07-05T07:22:24Z","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/2310.08008/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"BERT-based models have had strong performance on leaderboards, yet have been demonstrably worse in real-world settings requiring generalization. Limited quantities of training data is considered a key impediment to achieving generalizability in machine learning. In this paper, we examine the impact of training data quality, not quantity, on a model's generalizability. We consider two characteristics of training data: the portion of human-adversarial (h-adversarial), i.e., sample pairs with seemingly minor differences but different ground-truth labels, and human-affable (h-affable) training sam","authors_text":"Aparna Elangovan, Jiayuan He, Karin Verspoor, Yuan Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-10-12T03:20:43Z","title":"Effects of Human Adversarial and Affable Samples on BERT Generalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.08008","kind":"arxiv","version":4},"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:e9bf2009eb6c6b678de667d40ac1a8d31ab066f1804c787b6ad17fe1f5323979","target":"record","created_at":"2026-07-05T07:22:24Z","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":"54c50eb507b1bc522a0599222ecfefbbf24175e74ecd8e5adfb97b4d7e3cc758","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-10-12T03:20:43Z","title_canon_sha256":"fcd9727c49dd1403e359b53a61bbc0325a1a3ed14622037cf176aa5b9b00e27c"},"schema_version":"1.0","source":{"id":"2310.08008","kind":"arxiv","version":4}},"canonical_sha256":"cb7ef6470500522526d432cf8049173e8e2f2157ee78d9e4e49fa3c7cd539e05","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cb7ef6470500522526d432cf8049173e8e2f2157ee78d9e4e49fa3c7cd539e05","first_computed_at":"2026-07-05T07:22:24.939870Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:22:24.939870Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ph9sfyQxUHM2XVLBaDZOWMNY2mF1CluH+oNKXzTrFGutzS6X2CAb1KxScaPAkMND9sADI+yVqzLxMbpm8va5DA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:22:24.940352Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.08008","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e9bf2009eb6c6b678de667d40ac1a8d31ab066f1804c787b6ad17fe1f5323979","sha256:ac1b1421c8049a789cb5ae00084294ceca4dde96f0c062ddf5f7fd93f5fa5fbc"],"state_sha256":"314510e0a9410140fa5f14458e4f504185140e50d500997f738d1f6b02214230"}