{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:SOQPZRXL77KUN24COXVZIYL3QK","short_pith_number":"pith:SOQPZRXL","canonical_record":{"source":{"id":"1907.07802","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-17T22:51:33Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"3e21bf486ea5b8feeed0caca11307c35fb3400fba490bac7a260c11b7b9e4bfc","abstract_canon_sha256":"8d7e8e0d597e0b0b6e58b25fbe1f934553c27cd5c5b8ea2422f28457812f20b1"},"schema_version":"1.0"},"canonical_sha256":"93a0fcc6ebffd546eb8275eb94617b828da3e08051d3e94be6d3ed1193f50e8b","source":{"kind":"arxiv","id":"1907.07802","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.07802","created_at":"2026-05-17T23:40:16Z"},{"alias_kind":"arxiv_version","alias_value":"1907.07802v1","created_at":"2026-05-17T23:40:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.07802","created_at":"2026-05-17T23:40:16Z"},{"alias_kind":"pith_short_12","alias_value":"SOQPZRXL77KU","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"SOQPZRXL77KUN24C","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"SOQPZRXL","created_at":"2026-05-18T12:33:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:SOQPZRXL77KUN24COXVZIYL3QK","target":"record","payload":{"canonical_record":{"source":{"id":"1907.07802","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-17T22:51:33Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"3e21bf486ea5b8feeed0caca11307c35fb3400fba490bac7a260c11b7b9e4bfc","abstract_canon_sha256":"8d7e8e0d597e0b0b6e58b25fbe1f934553c27cd5c5b8ea2422f28457812f20b1"},"schema_version":"1.0"},"canonical_sha256":"93a0fcc6ebffd546eb8275eb94617b828da3e08051d3e94be6d3ed1193f50e8b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:16.262976Z","signature_b64":"iTjd0TRwv/D3LdEWe4QVs3xRnJ14Ff1zsfw47wontgR6dRQ+V4co22mXocrto38CvLRGkwAmZ4eiUzJIj4RMBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"93a0fcc6ebffd546eb8275eb94617b828da3e08051d3e94be6d3ed1193f50e8b","last_reissued_at":"2026-05-17T23:40:16.262219Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:16.262219Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.07802","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":"2026-05-17T23:40:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DEkVZuDaiA15nQwWTUjg6Mu3TZvBqsU3MNpihKlifYePkPKr/897JJpKfNQN5o3IKf8aDnDcIWCI40IB/AgbAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T15:51:18.693049Z"},"content_sha256":"23190cac6bb3aec6e93a8afee9f2e6e06dc498f7016adaa9e54757fa852c1c18","schema_version":"1.0","event_id":"sha256:23190cac6bb3aec6e93a8afee9f2e6e06dc498f7016adaa9e54757fa852c1c18"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:SOQPZRXL77KUN24COXVZIYL3QK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-Purposing Domain Adaptation Discriminators for Pseudo Labeling Confidence","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Diane J. Cook, Garrett Wilson","submitted_at":"2019-07-17T22:51:33Z","abstract_excerpt":"Often domain adaptation is performed using a discriminator (domain classifier) to learn domain-invariant feature representations so that a classifier trained on labeled source data will generalize well to unlabeled target data. A line of research stemming from semi-supervised learning uses pseudo labeling to directly generate \"pseudo labels\" for the unlabeled target data and trains a classifier on the now-labeled target data, where the samples are selected or weighted based on some measure of confidence. In this paper, we propose multi-purposing the discriminator to not only aid in producing d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.07802","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":"2026-05-17T23:40:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VLe/cgsyBbGtjzGgBmIAdldOcFma+btyMPyvjZC62kbobTjLTsXXFCnTsEMsjAk0U/0qLvsJA3APER/qw10DDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T15:51:18.693467Z"},"content_sha256":"e431de585ce3c070780f937a5cf2520da01058c8170251d66bdb5eaea3a1e8ae","schema_version":"1.0","event_id":"sha256:e431de585ce3c070780f937a5cf2520da01058c8170251d66bdb5eaea3a1e8ae"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SOQPZRXL77KUN24COXVZIYL3QK/bundle.json","state_url":"https://pith.science/pith/SOQPZRXL77KUN24COXVZIYL3QK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SOQPZRXL77KUN24COXVZIYL3QK/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":"2026-05-29T15:51:18Z","links":{"resolver":"https://pith.science/pith/SOQPZRXL77KUN24COXVZIYL3QK","bundle":"https://pith.science/pith/SOQPZRXL77KUN24COXVZIYL3QK/bundle.json","state":"https://pith.science/pith/SOQPZRXL77KUN24COXVZIYL3QK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SOQPZRXL77KUN24COXVZIYL3QK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:SOQPZRXL77KUN24COXVZIYL3QK","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":"8d7e8e0d597e0b0b6e58b25fbe1f934553c27cd5c5b8ea2422f28457812f20b1","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-17T22:51:33Z","title_canon_sha256":"3e21bf486ea5b8feeed0caca11307c35fb3400fba490bac7a260c11b7b9e4bfc"},"schema_version":"1.0","source":{"id":"1907.07802","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.07802","created_at":"2026-05-17T23:40:16Z"},{"alias_kind":"arxiv_version","alias_value":"1907.07802v1","created_at":"2026-05-17T23:40:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.07802","created_at":"2026-05-17T23:40:16Z"},{"alias_kind":"pith_short_12","alias_value":"SOQPZRXL77KU","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_16","alias_value":"SOQPZRXL77KUN24C","created_at":"2026-05-18T12:33:27Z"},{"alias_kind":"pith_short_8","alias_value":"SOQPZRXL","created_at":"2026-05-18T12:33:27Z"}],"graph_snapshots":[{"event_id":"sha256:e431de585ce3c070780f937a5cf2520da01058c8170251d66bdb5eaea3a1e8ae","target":"graph","created_at":"2026-05-17T23:40:16Z","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":"Often domain adaptation is performed using a discriminator (domain classifier) to learn domain-invariant feature representations so that a classifier trained on labeled source data will generalize well to unlabeled target data. A line of research stemming from semi-supervised learning uses pseudo labeling to directly generate \"pseudo labels\" for the unlabeled target data and trains a classifier on the now-labeled target data, where the samples are selected or weighted based on some measure of confidence. In this paper, we propose multi-purposing the discriminator to not only aid in producing d","authors_text":"Diane J. Cook, Garrett Wilson","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-17T22:51:33Z","title":"Multi-Purposing Domain Adaptation Discriminators for Pseudo Labeling Confidence"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.07802","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":"sha256:23190cac6bb3aec6e93a8afee9f2e6e06dc498f7016adaa9e54757fa852c1c18","target":"record","created_at":"2026-05-17T23:40:16Z","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":"8d7e8e0d597e0b0b6e58b25fbe1f934553c27cd5c5b8ea2422f28457812f20b1","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-07-17T22:51:33Z","title_canon_sha256":"3e21bf486ea5b8feeed0caca11307c35fb3400fba490bac7a260c11b7b9e4bfc"},"schema_version":"1.0","source":{"id":"1907.07802","kind":"arxiv","version":1}},"canonical_sha256":"93a0fcc6ebffd546eb8275eb94617b828da3e08051d3e94be6d3ed1193f50e8b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"93a0fcc6ebffd546eb8275eb94617b828da3e08051d3e94be6d3ed1193f50e8b","first_computed_at":"2026-05-17T23:40:16.262219Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:40:16.262219Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iTjd0TRwv/D3LdEWe4QVs3xRnJ14Ff1zsfw47wontgR6dRQ+V4co22mXocrto38CvLRGkwAmZ4eiUzJIj4RMBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:40:16.262976Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.07802","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:23190cac6bb3aec6e93a8afee9f2e6e06dc498f7016adaa9e54757fa852c1c18","sha256:e431de585ce3c070780f937a5cf2520da01058c8170251d66bdb5eaea3a1e8ae"],"state_sha256":"be4ca1814d1d5f64947f758b52fc7a2bb3ba1b5639d89d15ae36c81533b1e4cc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tcZeIaBWnyOmhhmq8E4MtzWyDVjyKk6/OEKQLkuyvdUyOLHDVQBoT+7arjCHiRAxlKAXu8+aKgIpbXf7h2YsCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-29T15:51:18.696793Z","bundle_sha256":"ebcb6703e10ae39f052f5938aa963da30f89faff9b386af8a61583ceb0bf4511"}}