{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:HNAOXMLTAIRUV4LHQWRDHIYWD3","short_pith_number":"pith:HNAOXMLT","canonical_record":{"source":{"id":"1702.07956","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-02-25T22:45:20Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"bc8528ddc0f150277d0d7e2984dcb8ec208762d7ace9d2c08f62b0f22ca77d54","abstract_canon_sha256":"8b9ac703a0d768f398d4c6cff16bd570c12285d02f994da4f51eb57594b1a9ab"},"schema_version":"1.0"},"canonical_sha256":"3b40ebb17302234af16785a233a3161efe4c960285671c131497edc3f358756f","source":{"kind":"arxiv","id":"1702.07956","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1702.07956","created_at":"2026-05-18T00:30:28Z"},{"alias_kind":"arxiv_version","alias_value":"1702.07956v5","created_at":"2026-05-18T00:30:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.07956","created_at":"2026-05-18T00:30:28Z"},{"alias_kind":"pith_short_12","alias_value":"HNAOXMLTAIRU","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"HNAOXMLTAIRUV4LH","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"HNAOXMLT","created_at":"2026-05-18T12:31:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:HNAOXMLTAIRUV4LHQWRDHIYWD3","target":"record","payload":{"canonical_record":{"source":{"id":"1702.07956","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-02-25T22:45:20Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"bc8528ddc0f150277d0d7e2984dcb8ec208762d7ace9d2c08f62b0f22ca77d54","abstract_canon_sha256":"8b9ac703a0d768f398d4c6cff16bd570c12285d02f994da4f51eb57594b1a9ab"},"schema_version":"1.0"},"canonical_sha256":"3b40ebb17302234af16785a233a3161efe4c960285671c131497edc3f358756f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:30:28.478347Z","signature_b64":"W8vt8bsl5wRuqAdzP9CxkzSpPjN5Ugvc5JaFgCpNOCq5wlR3uH7aOI8nWhOjaPi3LXvstCibR7j9UA4zaGapDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3b40ebb17302234af16785a233a3161efe4c960285671c131497edc3f358756f","last_reissued_at":"2026-05-18T00:30:28.477833Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:30:28.477833Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1702.07956","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:30:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kdoffzMWvUjgO2PeJ99Zu5TOFLoH6au73pOZM4eyNVt9gPcDyp8pU6rK/AejDpL/s3M2lZZAurFlaMiuc1aWAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T13:33:44.049836Z"},"content_sha256":"8747207319097e3da5be00ee95c6c9d324b2ad91d3523b91e4005996ea5488f4","schema_version":"1.0","event_id":"sha256:8747207319097e3da5be00ee95c6c9d324b2ad91d3523b91e4005996ea5488f4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:HNAOXMLTAIRUV4LHQWRDHIYWD3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generative Adversarial Active Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Jia-Jie Zhu, Jos\\'e Bento","submitted_at":"2017-02-25T22:45:20Z","abstract_excerpt":"We propose a new active learning by query synthesis approach using Generative Adversarial Networks (GAN). Different from regular active learning, the resulting algorithm adaptively synthesizes training instances for querying to increase learning speed. We generate queries according to the uncertainty principle, but our idea can work with other active learning principles. We report results from various numerical experiments to demonstrate the effectiveness the proposed approach. In some settings, the proposed algorithm outperforms traditional pool-based approaches. To the best our knowledge, th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.07956","kind":"arxiv","version":5},"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":"2026-05-18T00:30:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SnwB5MTRsvF2+mg+udNvwNz1ALTBQrH1Ya1+0RRp2E3NYJTQfTQCEGx1y4B39dOY+dq5wDH1XojUl6y0eNs+Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T13:33:44.050385Z"},"content_sha256":"fd5b41aaf69ad961799b27993c598778cf1ec094e7ecb5f473efbea1e684d3c2","schema_version":"1.0","event_id":"sha256:fd5b41aaf69ad961799b27993c598778cf1ec094e7ecb5f473efbea1e684d3c2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HNAOXMLTAIRUV4LHQWRDHIYWD3/bundle.json","state_url":"https://pith.science/pith/HNAOXMLTAIRUV4LHQWRDHIYWD3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HNAOXMLTAIRUV4LHQWRDHIYWD3/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":"2026-05-31T13:33:44Z","links":{"resolver":"https://pith.science/pith/HNAOXMLTAIRUV4LHQWRDHIYWD3","bundle":"https://pith.science/pith/HNAOXMLTAIRUV4LHQWRDHIYWD3/bundle.json","state":"https://pith.science/pith/HNAOXMLTAIRUV4LHQWRDHIYWD3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HNAOXMLTAIRUV4LHQWRDHIYWD3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:HNAOXMLTAIRUV4LHQWRDHIYWD3","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":"8b9ac703a0d768f398d4c6cff16bd570c12285d02f994da4f51eb57594b1a9ab","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-02-25T22:45:20Z","title_canon_sha256":"bc8528ddc0f150277d0d7e2984dcb8ec208762d7ace9d2c08f62b0f22ca77d54"},"schema_version":"1.0","source":{"id":"1702.07956","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1702.07956","created_at":"2026-05-18T00:30:28Z"},{"alias_kind":"arxiv_version","alias_value":"1702.07956v5","created_at":"2026-05-18T00:30:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.07956","created_at":"2026-05-18T00:30:28Z"},{"alias_kind":"pith_short_12","alias_value":"HNAOXMLTAIRU","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"HNAOXMLTAIRUV4LH","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"HNAOXMLT","created_at":"2026-05-18T12:31:18Z"}],"graph_snapshots":[{"event_id":"sha256:fd5b41aaf69ad961799b27993c598778cf1ec094e7ecb5f473efbea1e684d3c2","target":"graph","created_at":"2026-05-18T00:30:28Z","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":"We propose a new active learning by query synthesis approach using Generative Adversarial Networks (GAN). Different from regular active learning, the resulting algorithm adaptively synthesizes training instances for querying to increase learning speed. We generate queries according to the uncertainty principle, but our idea can work with other active learning principles. We report results from various numerical experiments to demonstrate the effectiveness the proposed approach. In some settings, the proposed algorithm outperforms traditional pool-based approaches. To the best our knowledge, th","authors_text":"Jia-Jie Zhu, Jos\\'e Bento","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-02-25T22:45:20Z","title":"Generative Adversarial Active Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.07956","kind":"arxiv","version":5},"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":"sha256:8747207319097e3da5be00ee95c6c9d324b2ad91d3523b91e4005996ea5488f4","target":"record","created_at":"2026-05-18T00:30:28Z","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":"8b9ac703a0d768f398d4c6cff16bd570c12285d02f994da4f51eb57594b1a9ab","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-02-25T22:45:20Z","title_canon_sha256":"bc8528ddc0f150277d0d7e2984dcb8ec208762d7ace9d2c08f62b0f22ca77d54"},"schema_version":"1.0","source":{"id":"1702.07956","kind":"arxiv","version":5}},"canonical_sha256":"3b40ebb17302234af16785a233a3161efe4c960285671c131497edc3f358756f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3b40ebb17302234af16785a233a3161efe4c960285671c131497edc3f358756f","first_computed_at":"2026-05-18T00:30:28.477833Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:30:28.477833Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"W8vt8bsl5wRuqAdzP9CxkzSpPjN5Ugvc5JaFgCpNOCq5wlR3uH7aOI8nWhOjaPi3LXvstCibR7j9UA4zaGapDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:30:28.478347Z","signed_message":"canonical_sha256_bytes"},"source_id":"1702.07956","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8747207319097e3da5be00ee95c6c9d324b2ad91d3523b91e4005996ea5488f4","sha256:fd5b41aaf69ad961799b27993c598778cf1ec094e7ecb5f473efbea1e684d3c2"],"state_sha256":"13f8527bed203c42edb1d4a0fff35acdc771c835add8cace21dbdb965ab05ad3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZDs7x5Zy1ALip4FrzAkUPfqSQcR8ibxhSOULw+qk6zbt4cjW0tI2etI3YeHWmozICM2JbjoWnLSRBkWL1BU1Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T13:33:44.053880Z","bundle_sha256":"1908124bd80fbb370be8b9a8ee02b44d4b6a7139f36106ca41973f4d7100acb0"}}