{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:UG5YIDSPIIPEVFUJVJZ6GKFVL6","short_pith_number":"pith:UG5YIDSP","canonical_record":{"source":{"id":"1807.00392","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-07-01T20:46:20Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"fa610c7bdd50abcdc7215a0b13474263086fb7b455cfc386f36c812399dd743d","abstract_canon_sha256":"3b1ef4bacac9eca9d3af3b028e5c3037d4c5cd4e332b39a2756ffbc3339ceeb3"},"schema_version":"1.0"},"canonical_sha256":"a1bb840e4f421e4a9689aa73e328b55fb5f621960c8070c6a8e231fa6b95169d","source":{"kind":"arxiv","id":"1807.00392","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.00392","created_at":"2026-05-18T00:11:55Z"},{"alias_kind":"arxiv_version","alias_value":"1807.00392v1","created_at":"2026-05-18T00:11:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.00392","created_at":"2026-05-18T00:11:55Z"},{"alias_kind":"pith_short_12","alias_value":"UG5YIDSPIIPE","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"UG5YIDSPIIPEVFUJ","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"UG5YIDSP","created_at":"2026-05-18T12:32:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:UG5YIDSPIIPEVFUJVJZ6GKFVL6","target":"record","payload":{"canonical_record":{"source":{"id":"1807.00392","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-07-01T20:46:20Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"fa610c7bdd50abcdc7215a0b13474263086fb7b455cfc386f36c812399dd743d","abstract_canon_sha256":"3b1ef4bacac9eca9d3af3b028e5c3037d4c5cd4e332b39a2756ffbc3339ceeb3"},"schema_version":"1.0"},"canonical_sha256":"a1bb840e4f421e4a9689aa73e328b55fb5f621960c8070c6a8e231fa6b95169d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:11:55.015457Z","signature_b64":"E79yRWcMDgYPOl2peulWUHo9OSAh0Ss20eMhWMPY2L3OVjQMySuzP9rkDdFz2lWiLjmrrXBjxBlAKVmsOFNDCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a1bb840e4f421e4a9689aa73e328b55fb5f621960c8070c6a8e231fa6b95169d","last_reissued_at":"2026-05-18T00:11:55.014868Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:11:55.014868Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1807.00392","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":"2026-05-18T00:11:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kyQ+TmOfoAm/lk0hJK77dYnX6f5uBFlJ0V7ScukkeS4+yuZqrJZwIJFneMcb274zSb02i4U4d8jx78h6kVdTAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T19:40:30.394500Z"},"content_sha256":"d6cc91061d3f0596e4b14d42b75aed3168e548157c008641a65cd50af9edf733","schema_version":"1.0","event_id":"sha256:d6cc91061d3f0596e4b14d42b75aed3168e548157c008641a65cd50af9edf733"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:UG5YIDSPIIPEVFUJVJZ6GKFVL6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Gradient Reversal Against Discrimination","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"stat.ML","authors_text":"Edward Raff, Jared Sylvester","submitted_at":"2018-07-01T20:46:20Z","abstract_excerpt":"No methods currently exist for making arbitrary neural networks fair. In this work we introduce GRAD, a new and simplified method to producing fair neural networks that can be used for auto-encoding fair representations or directly with predictive networks. It is easy to implement and add to existing architectures, has only one (insensitive) hyper-parameter, and provides improved individual and group fairness. We use the flexibility of GRAD to demonstrate multi-attribute protection."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.00392","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":""},"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":"2026-05-18T00:11:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ds8Nf86QLP1kMrLoqqxqyU2zukcVC0i8xAoDb6JIgTnWyqoTN6sFTdn8useE8jKD0mNDfwCu5wWxzF61aXiVBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T19:40:30.395125Z"},"content_sha256":"5a63b07f63be77a0a715af505e52c18c2ca9598e5ec2ea34484f9cb38ffe3bde","schema_version":"1.0","event_id":"sha256:5a63b07f63be77a0a715af505e52c18c2ca9598e5ec2ea34484f9cb38ffe3bde"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UG5YIDSPIIPEVFUJVJZ6GKFVL6/bundle.json","state_url":"https://pith.science/pith/UG5YIDSPIIPEVFUJVJZ6GKFVL6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UG5YIDSPIIPEVFUJVJZ6GKFVL6/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":"2026-06-05T19:40:30Z","links":{"resolver":"https://pith.science/pith/UG5YIDSPIIPEVFUJVJZ6GKFVL6","bundle":"https://pith.science/pith/UG5YIDSPIIPEVFUJVJZ6GKFVL6/bundle.json","state":"https://pith.science/pith/UG5YIDSPIIPEVFUJVJZ6GKFVL6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UG5YIDSPIIPEVFUJVJZ6GKFVL6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:UG5YIDSPIIPEVFUJVJZ6GKFVL6","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":"3b1ef4bacac9eca9d3af3b028e5c3037d4c5cd4e332b39a2756ffbc3339ceeb3","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-07-01T20:46:20Z","title_canon_sha256":"fa610c7bdd50abcdc7215a0b13474263086fb7b455cfc386f36c812399dd743d"},"schema_version":"1.0","source":{"id":"1807.00392","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.00392","created_at":"2026-05-18T00:11:55Z"},{"alias_kind":"arxiv_version","alias_value":"1807.00392v1","created_at":"2026-05-18T00:11:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.00392","created_at":"2026-05-18T00:11:55Z"},{"alias_kind":"pith_short_12","alias_value":"UG5YIDSPIIPE","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"UG5YIDSPIIPEVFUJ","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"UG5YIDSP","created_at":"2026-05-18T12:32:56Z"}],"graph_snapshots":[{"event_id":"sha256:5a63b07f63be77a0a715af505e52c18c2ca9598e5ec2ea34484f9cb38ffe3bde","target":"graph","created_at":"2026-05-18T00:11:55Z","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"},"paper":{"abstract_excerpt":"No methods currently exist for making arbitrary neural networks fair. In this work we introduce GRAD, a new and simplified method to producing fair neural networks that can be used for auto-encoding fair representations or directly with predictive networks. It is easy to implement and add to existing architectures, has only one (insensitive) hyper-parameter, and provides improved individual and group fairness. We use the flexibility of GRAD to demonstrate multi-attribute protection.","authors_text":"Edward Raff, Jared Sylvester","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-07-01T20:46:20Z","title":"Gradient Reversal Against Discrimination"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.00392","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:d6cc91061d3f0596e4b14d42b75aed3168e548157c008641a65cd50af9edf733","target":"record","created_at":"2026-05-18T00:11:55Z","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":"3b1ef4bacac9eca9d3af3b028e5c3037d4c5cd4e332b39a2756ffbc3339ceeb3","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-07-01T20:46:20Z","title_canon_sha256":"fa610c7bdd50abcdc7215a0b13474263086fb7b455cfc386f36c812399dd743d"},"schema_version":"1.0","source":{"id":"1807.00392","kind":"arxiv","version":1}},"canonical_sha256":"a1bb840e4f421e4a9689aa73e328b55fb5f621960c8070c6a8e231fa6b95169d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a1bb840e4f421e4a9689aa73e328b55fb5f621960c8070c6a8e231fa6b95169d","first_computed_at":"2026-05-18T00:11:55.014868Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:11:55.014868Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"E79yRWcMDgYPOl2peulWUHo9OSAh0Ss20eMhWMPY2L3OVjQMySuzP9rkDdFz2lWiLjmrrXBjxBlAKVmsOFNDCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:11:55.015457Z","signed_message":"canonical_sha256_bytes"},"source_id":"1807.00392","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d6cc91061d3f0596e4b14d42b75aed3168e548157c008641a65cd50af9edf733","sha256:5a63b07f63be77a0a715af505e52c18c2ca9598e5ec2ea34484f9cb38ffe3bde"],"state_sha256":"f1209fa49b9d07b9a058f64da7a570eed8bdd5f360ee5b40777425be115dc6f2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bJ0EHwuCVeQLj8xBjiVFq6ZB+qDR0GUXxU/1m6pqM7ZuaW7KtmA8GU5TAfoBegUCuwUVKMNUsj4gbA34PDKeBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T19:40:30.399396Z","bundle_sha256":"a439dd58d2c9fe5f69c6c98aac136ca86418122fc0ee0793c0de2786b7fe950f"}}