{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:MLFBLOWJOAHCC6QLTG2PX4HYOU","short_pith_number":"pith:MLFBLOWJ","canonical_record":{"source":{"id":"2502.11031","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-16T07:55:19Z","cross_cats_sorted":[],"title_canon_sha256":"dff71ce0fab5dce073b452213179247391eb78921e573dec7bae81e8425e3cf7","abstract_canon_sha256":"6c6a106ea9170955eaca6149530a285bd71e813ef564c0d38e6c42159c4b59a6"},"schema_version":"1.0"},"canonical_sha256":"62ca15bac9700e217a0b99b4fbf0f87517b16a807f9fdbf560c9ba5b35497231","source":{"kind":"arxiv","id":"2502.11031","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.11031","created_at":"2026-07-05T10:15:02Z"},{"alias_kind":"arxiv_version","alias_value":"2502.11031v1","created_at":"2026-07-05T10:15:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.11031","created_at":"2026-07-05T10:15:02Z"},{"alias_kind":"pith_short_12","alias_value":"MLFBLOWJOAHC","created_at":"2026-07-05T10:15:02Z"},{"alias_kind":"pith_short_16","alias_value":"MLFBLOWJOAHCC6QL","created_at":"2026-07-05T10:15:02Z"},{"alias_kind":"pith_short_8","alias_value":"MLFBLOWJ","created_at":"2026-07-05T10:15:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:MLFBLOWJOAHCC6QLTG2PX4HYOU","target":"record","payload":{"canonical_record":{"source":{"id":"2502.11031","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-16T07:55:19Z","cross_cats_sorted":[],"title_canon_sha256":"dff71ce0fab5dce073b452213179247391eb78921e573dec7bae81e8425e3cf7","abstract_canon_sha256":"6c6a106ea9170955eaca6149530a285bd71e813ef564c0d38e6c42159c4b59a6"},"schema_version":"1.0"},"canonical_sha256":"62ca15bac9700e217a0b99b4fbf0f87517b16a807f9fdbf560c9ba5b35497231","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:15:02.713904Z","signature_b64":"SUgDgUQ5FL6e6e7j/YQ2oGggsASEnGJHZwG3N9qU4EphcAhl/MCuurjl3mQDEgmKNBPISBcw4sfIcDft9T5eDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"62ca15bac9700e217a0b99b4fbf0f87517b16a807f9fdbf560c9ba5b35497231","last_reissued_at":"2026-07-05T10:15:02.713505Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:15:02.713505Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.11031","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":"2026-07-05T10:15:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"unCVoXJp5uxXfA1wlpYvOiYcTbwz4YlERcxhm60fYM0k+qAkT+KtWuEKrmGrJc8ec7B5qqRs9aB3PiOQ4ubYAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T05:02:41.172238Z"},"content_sha256":"f63b5980f25f53e588c1499dd2ad047a6ef829eeeebb7255c79adc2c2230ad7f","schema_version":"1.0","event_id":"sha256:f63b5980f25f53e588c1499dd2ad047a6ef829eeeebb7255c79adc2c2230ad7f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:MLFBLOWJOAHCC6QLTG2PX4HYOU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Critical Review of Predominant Bias in Neural Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Hanchen Xie, Jiageng Zhu, Jiazhi Li, Mahyar Khayatkhoei, Mohamed E. Hussein, Wael AbdAlmageed","submitted_at":"2025-02-16T07:55:19Z","abstract_excerpt":"Bias issues of neural networks garner significant attention along with its promising advancement. Among various bias issues, mitigating two predominant biases is crucial in advancing fair and trustworthy AI: (1) ensuring neural networks yields even performance across demographic groups, and (2) ensuring algorithmic decision-making does not rely on protected attributes. However, upon the investigation of \\pc papers in the relevant literature, we find that there exists a persistent, extensive but under-explored confusion regarding these two types of biases. Furthermore, the confusion has already"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.11031","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/2502.11031/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":"2026-07-05T10:15:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G3dtSBLZBx6pWgAM94MsM+dGubi7PPn6ehoc4WzRx5y9PImI76DQbg4FyQI1kSyIXrNITh7UiPH7EeT4oIG6Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T05:02:41.172627Z"},"content_sha256":"d7ae7ac80e9cbbbeecd1e3c8eeb8ca79334aab441bb09ce5cb75ebeab65875d3","schema_version":"1.0","event_id":"sha256:d7ae7ac80e9cbbbeecd1e3c8eeb8ca79334aab441bb09ce5cb75ebeab65875d3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MLFBLOWJOAHCC6QLTG2PX4HYOU/bundle.json","state_url":"https://pith.science/pith/MLFBLOWJOAHCC6QLTG2PX4HYOU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MLFBLOWJOAHCC6QLTG2PX4HYOU/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":"2026-07-09T05:02:41Z","links":{"resolver":"https://pith.science/pith/MLFBLOWJOAHCC6QLTG2PX4HYOU","bundle":"https://pith.science/pith/MLFBLOWJOAHCC6QLTG2PX4HYOU/bundle.json","state":"https://pith.science/pith/MLFBLOWJOAHCC6QLTG2PX4HYOU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MLFBLOWJOAHCC6QLTG2PX4HYOU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:MLFBLOWJOAHCC6QLTG2PX4HYOU","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":"6c6a106ea9170955eaca6149530a285bd71e813ef564c0d38e6c42159c4b59a6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-16T07:55:19Z","title_canon_sha256":"dff71ce0fab5dce073b452213179247391eb78921e573dec7bae81e8425e3cf7"},"schema_version":"1.0","source":{"id":"2502.11031","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.11031","created_at":"2026-07-05T10:15:02Z"},{"alias_kind":"arxiv_version","alias_value":"2502.11031v1","created_at":"2026-07-05T10:15:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.11031","created_at":"2026-07-05T10:15:02Z"},{"alias_kind":"pith_short_12","alias_value":"MLFBLOWJOAHC","created_at":"2026-07-05T10:15:02Z"},{"alias_kind":"pith_short_16","alias_value":"MLFBLOWJOAHCC6QL","created_at":"2026-07-05T10:15:02Z"},{"alias_kind":"pith_short_8","alias_value":"MLFBLOWJ","created_at":"2026-07-05T10:15:02Z"}],"graph_snapshots":[{"event_id":"sha256:d7ae7ac80e9cbbbeecd1e3c8eeb8ca79334aab441bb09ce5cb75ebeab65875d3","target":"graph","created_at":"2026-07-05T10:15:02Z","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/2502.11031/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Bias issues of neural networks garner significant attention along with its promising advancement. Among various bias issues, mitigating two predominant biases is crucial in advancing fair and trustworthy AI: (1) ensuring neural networks yields even performance across demographic groups, and (2) ensuring algorithmic decision-making does not rely on protected attributes. However, upon the investigation of \\pc papers in the relevant literature, we find that there exists a persistent, extensive but under-explored confusion regarding these two types of biases. Furthermore, the confusion has already","authors_text":"Hanchen Xie, Jiageng Zhu, Jiazhi Li, Mahyar Khayatkhoei, Mohamed E. Hussein, Wael AbdAlmageed","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-16T07:55:19Z","title":"A Critical Review of Predominant Bias in Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.11031","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:f63b5980f25f53e588c1499dd2ad047a6ef829eeeebb7255c79adc2c2230ad7f","target":"record","created_at":"2026-07-05T10:15:02Z","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":"6c6a106ea9170955eaca6149530a285bd71e813ef564c0d38e6c42159c4b59a6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-16T07:55:19Z","title_canon_sha256":"dff71ce0fab5dce073b452213179247391eb78921e573dec7bae81e8425e3cf7"},"schema_version":"1.0","source":{"id":"2502.11031","kind":"arxiv","version":1}},"canonical_sha256":"62ca15bac9700e217a0b99b4fbf0f87517b16a807f9fdbf560c9ba5b35497231","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"62ca15bac9700e217a0b99b4fbf0f87517b16a807f9fdbf560c9ba5b35497231","first_computed_at":"2026-07-05T10:15:02.713505Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:15:02.713505Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SUgDgUQ5FL6e6e7j/YQ2oGggsASEnGJHZwG3N9qU4EphcAhl/MCuurjl3mQDEgmKNBPISBcw4sfIcDft9T5eDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:15:02.713904Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.11031","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f63b5980f25f53e588c1499dd2ad047a6ef829eeeebb7255c79adc2c2230ad7f","sha256:d7ae7ac80e9cbbbeecd1e3c8eeb8ca79334aab441bb09ce5cb75ebeab65875d3"],"state_sha256":"b7698bbd161f29021e640e12ecad505fd5d7cd17aaa8624e653e9a2181cf8fda"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iL/gDKfOHcgvpns3S56K8VNPC6cXCwsDFiAbIfXKnsM6p7UOSEmFcaVYtxg1+RogxKJQWrTYe//8qMWfxQdpBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T05:02:41.174603Z","bundle_sha256":"7934dfa247d4b7b909d0f9e23261de4076621301d6c566b07022119cdeaf6602"}}